Alternatives to Tuning Engines

Compare Tuning Engines alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Tuning Engines in 2026. Compare features, ratings, user reviews, pricing, and more from Tuning Engines competitors and alternatives in order to make an informed decision for your business.

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    Gemini Enterprise Agent Platform
    Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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    Preloop

    Preloop

    Preloop

    Preloop is the open source AI agent control plane for agents that take real actions. It combines an MCP firewall for tool access, an AI model gateway for cost, safety, and attribution, policy-as-code with human approvals, runtime session observability, and audit trails in a single self-hostable platform. AI agents can deploy code, change infrastructure, move money, touch production data, and burn model spend in seconds, so Preloop helps teams control what agents can do, how much they spend, and which actions require human approval. It works with OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any MCP-compatible agent or managed runtime. Access rules can inspect arguments and context, not just tool names, with CEL expressions for fine-grained conditions. Teams can start with observability, then layer in approvals and deny rules without SDKs or invasive app changes.
    Starting Price: $290 per month
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    Big Pickle

    Big Pickle

    OpenCode

    Big Pickle is an AI model available through OpenCode Zen, a curated model provider focused on coding-agent workflows. The model is designed for text-based input, reasoning tasks, function calling, and developer workflows that require long-context understanding. Big Pickle supports a large context window, making it useful for working across bigger codebases, project files, technical prompts, and multi-step coding tasks. It can be accessed through OpenCode Zen using an OpenAI-compatible API format, allowing developers to integrate it into agentic coding tools and automation workflows. The model is positioned as a free or low-cost option within OpenCode’s coding-agent ecosystem. Big Pickle helps developers experiment with AI-assisted coding, reasoning, tool use, and long-context automation without relying only on premium frontier models.
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    Core42

    Core42

    Core42

    Core42 delivers sovereign AI and cloud solutions that help individuals, enterprises, and nations unlock the full potential of AI through secure, scalable, and performance-driven infrastructure. Its AI Cloud is a full-stack platform built for the entire intelligence lifecycle, from data movement and training to optimization, fine-tuning, deployment, governance, and production inference. It gives AI builders access to leading accelerators, integrated tools, orchestration, high-performance storage, and expert support so they can train, fine-tune, and deploy agentic and inference workloads faster. Core42 AI Cloud supports GenAI services, model hosting and inference, AI operations, and infrastructure as a service, enabling teams to build and scale next-generation AI applications with confidence and speed. Its GenAI services help accelerate innovation with agents, retrieval-augmented generation, guardrails, and fine-tuning.
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    Dynamiq

    Dynamiq

    Dynamiq

    Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your own
    Starting Price: $125/month
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    Unity AI Gateway
    Unity AI Gateway provides centralized governance, observability, and spend controls across enterprise AI systems, helping organizations manage agents, tools, models, MCPs, and AI frameworks from a single governed layer. It applies consistent governance across Databricks-hosted AI, external models, coding agents, agent harnesses, and other AI services without locking teams into a single provider or stack. Identity-aware policies control what agents can access, which actions they can take, and which tools they can use, while built-in, custom, and third-party guardrails enforce safety and compliance across prompts, responses, and interactions. It captures prompts, traces, tool calls, payload logs, audit logs, token usage, and policy decisions to monitor behavior, investigate incidents, and support compliance. Centralized cost controls track consumption across users, teams, applications, agents, and providers, with budgets, rate limits, and hard spend caps.
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    UnoRouter

    UnoRouter

    UnoRouter

    UnoRouter is an OpenAI-compatible LLM gateway. One API key gives you 200+ models across providers (OpenAI, Anthropic, Google and more), drop-in for coding agents like Claude Code, Cline, Codex and Kilo Code. Point any OpenAI SDK at the base URL and switch models without changing code. UnoRouter also includes a built-in chat and character client (personas, lorebooks, SillyTavern card import) on the same key. Usage-based pricing with a free tier, live model and price data.
    Starting Price: Free tier, usage-based
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    OpenCode Go

    OpenCode Go

    OpenCode

    OpenCode Go brings agentic coding to programmers around the world by providing reliable access to a curated lineup of capable open coding models. It is designed primarily for international users and focuses on stable global access, generous usage limits, and models tested specifically for coding-agent workloads. Open models have reached performance close to proprietary models for coding tasks, but provider quality, latency, and availability can vary. To address this, the OpenCode team tests selected models, works with model teams and providers to determine how they should be served, and benchmarks each model-provider combination before recommending it. Go works like any other provider in OpenCode, users connect with an API key and can view the available models directly in the interface. It is completely optional and can also be used with other coding agents, helping avoid lock-in.
    Starting Price: $10 per month
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    Spawn

    Spawn

    OpenRouter

    Spawn is an experimental OpenRouter tool for deploying AI coding agents on your own infrastructure with a single command. Pick an agent, choose a cloud, and Spawn provisions a virtual machine, installs the agent and its dependencies, authenticates to OpenRouter and the cloud using a CLI OAuth flow, configures endpoints and model routing, and then opens an SSH session so you can start working. Each agent-and-cloud combination is implemented as a self-contained script, avoiding Terraform and YAML while keeping deployment portable. Supported agents include Claude Code, OpenClaw, Codex CLI, OpenCode, Kilo Code, Hermes Agent, Junie, Pi, Cursor CLI, and T3 Code, making it easy to explore coding-agent workflows or switch between them with one command. Spawn supports cloud environments such as DigitalOcean, Sprite, Hetzner Cloud, AWS Lightsail, GCP Compute Engine, and Daytona, as well as a local machine or a throwaway local Docker sandbox.
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    Tinfoil

    Tinfoil

    Tinfoil

    Tinfoil is a verifiably private AI platform built to deliver zero-trust, zero-data-retention inference by running open-source or custom models inside secure hardware enclaves in the cloud, giving you the data-privacy assurances of on-premises systems with the scalability and convenience of the cloud. All user inputs and inference operations are processed in confidential-computing environments so that no one, not even Tinfoil or the cloud provider, can access or retain your data. It supports private chat, private data analysis, user-trained fine-tuning, and an OpenAI-compatible inference API, covers workloads such as AI agents, private content moderation, and proprietary code models, and provides features like public verification of enclave attestation, “provable zero data access,” and full compatibility with major open source models.
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    Cline

    Cline

    Cline AI Coding Agent

    Cline is an open-source AI coding agent that helps developers understand, modify, and automate software development tasks directly from their IDE, terminal, or embedded applications. The platform supports coordinated code editing, bash command execution, planning, and autonomous workflows while giving developers control over every step of the process. Cline works with major AI models including Claude, GPT, Gemini, Mistral, DeepSeek, Ollama, and any OpenAI-compatible API without locking users into a single provider. Developers can use Cline to refactor large codebases, automate repetitive engineering tasks, integrate with CI/CD pipelines, and extend functionality through plugins and the Model Context Protocol (MCP). The platform also supports custom coding rules, reusable skills, multi-agent collaboration, and scheduled automations for complex software projects.
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    BenchGen

    BenchGen

    BenchGen

    BenchGen is the learning infrastructure for AI agents: an open platform where developers discover benchmarks and RL environments, evaluate their complete agent system — model and harness together — against verifiable rewards, and export clean trajectory data for fine-tuning. One loop: benchmark → evaluate → fine-tune → re-evaluate.
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    Tülu 3
    Tülu 3 is an advanced instruction-following language model developed by the Allen Institute for AI (Ai2), designed to enhance capabilities in areas such as knowledge, reasoning, mathematics, coding, and safety. Built upon the Llama 3 Base, Tülu 3 employs a comprehensive four-stage post-training process: meticulous prompt curation and synthesis, supervised fine-tuning on a diverse set of prompts and completions, preference tuning using both off- and on-policy data, and a novel reinforcement learning approach to bolster specific skills with verifiable rewards. This open-source model distinguishes itself by providing full transparency, including access to training data, code, and evaluation tools, thereby closing the performance gap between open and proprietary fine-tuning methods. Evaluations indicate that Tülu 3 outperforms other open-weight models of similar size, such as Llama 3.1-Instruct and Qwen2.5-Instruct, across various benchmarks.
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    ZGI

    ZGI

    ZGI

    ZGI is an open source enterprise AI platform for building business-ready agents with company data, tools, workflows, models, and skills. Its Agent Runtime lets agents load Skills, use company knowledge and live data, call tools, and return useful work fast. The Model Gateway connects global and domestic providers such as OpenAI, Anthropic, Google, DeepSeek, and Qwen, allowing teams to choose the right model for each agent by quality, availability, cost, or region while centrally controlling access, quotas, routing policies, and fallback. The product workspace covers the full agent lifecycle: Agent Studio combines Skills, knowledge, tools, and models; Workflows orchestrate multi-step work and let users inspect every execution; Database supports natural-language queries over live business data with governed access; Model Management handles provider connections and enterprise routing; and Knowledge Assets turn company files into searchable, source-aware knowledge.
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    Mistral AI Studio
    Mistral AI Studio is a unified builder-platform that enables organizations and development teams to design, customize, deploy, and manage advanced AI agents, models, and workflows from proof-of-concept through to production. The platform offers reusable blocks, including agents, tools, connectors, guardrails, datasets, workflows, and evaluations, combined with observability and telemetry capabilities so you can track agent performance, trace root causes, and govern production AI operations with visibility. With modules like Agent Runtime to make multi-step AI behaviors repeatable and shareable, AI Registry to catalogue and manage model assets, and Data & Tool Connections for seamless integration with enterprise systems, Studio supports everything from fine-tuning open source models to embedding them in your infrastructure and rolling out enterprise-grade AI solutions.
    Starting Price: $14.99 per month
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    NeevCloud

    NeevCloud

    NeevCloud

    NeevCloud is a full-stack AI SuperCloud for building, training, fine-tuning, and deploying AI models at scale. Access GPU AI Services powered by NVIDIA H100, B200, and GB200 NVL72; a pay-per-token Model API supporting Llama 3, Mixtral, Qwen, and Stable Diffusion; and Agentic Studio for building, testing, and shipping AI agents with built-in governance and observability. The platform is Kubernetes-native, OpenAI-compatible, and designed for zero lock-in with no egress fees and transparent pricing. Cloud Servers, Snapshots, Load Balancers, and Orchestration round out the IaaS layer. S3-compatible object storage is available through Zata.ai. NeevCloud owns every infrastructure layer, from GPU clusters to AI orchestration software, delivering strong price-to-performance, data sovereignty, and instant GPU access with no waiting lists. Built for AI startups, ML engineers, data scientists, enterprises, and research institutions scaling AI workloads.
    Starting Price: $1.69/GPU/hour
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    GLM Coding Plan
    Z.ai DevPack (GLM Coding Plan) is a subscription-based AI coding platform designed to integrate high-performance language models into existing development tools, enabling a faster, more intelligent, and stable coding workflow. It provides access to advanced models such as GLM-4.7 and GLM-5, which can be used across popular AI coding environments like Claude Code, Cline, OpenCode, and other tools that support OpenAI-compatible APIs. The system allows developers to use natural language programming to describe requirements and automatically generate code, debug issues, and execute tasks, while also offering real-time, context-aware code completion to improve productivity. It includes intelligent debugging and repair capabilities, enabling models to analyze errors, suggest fixes, and maintain smooth execution throughout development. DevPack is designed with a structured interface that AI agents can understand, allowing seamless interaction between tools and models.
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    Fastino

    Fastino

    Fastino

    Fastino is an applied AI platform focused on specialized, open-weight language models and the Fastino Fine-Tuning Agent. The agent lets users describe a task in plain language, then automatically selects the architecture, generates training data, trains and evaluates the model, and returns a task-specific model ready to deploy. Fine-tuning projects can be created and revisited from one interface, with models trained on the user’s terms and deployable in their own environment. The resulting models are designed for production-grade performance, with typical response times under 50 ms, while model weights remain private and owned by the user. Models can move from a task description to a trained result in hours, giving teams a faster path to specialized deployment. Fastino also provides open-source and open-weight models for specialized AI workloads.
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    distil labs

    distil labs

    distil labs

    distil labs optimizes AI workloads by replacing expensive frontier-model calls with custom small language models tuned to a specific task while maintaining the required quality bar. It observes real production traffic, captures traces from existing LLM requests, and automatically builds an evaluation set to understand how the workload actually behaves. It then generates and validates synthetic training data, matches the data distribution to the target workload, performs supervised fine-tuning and reinforcement learning, quantizes the model, and deploys an optimized endpoint. Results are automatically evaluated against the current model on accuracy, latency, and efficiency before teams choose to scale traffic. The resulting OpenAI-compatible endpoint combines a specialized SLM, prompt optimization, caching, and tuned serving for the use case.
    Starting Price: $0.04 per 1M tokens
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    AIHubMix

    AIHubMix

    AIHubMix

    AIHubMix is an AI model API routing service that provides access to major language and multimodal models through one unified interface. It uses the OpenAI API format as its standard, allowing developers to connect with an AIHubMix API key and forwarding base URL, then switch between supported models simply by changing the model ID. It supports OpenAI-compatible, Anthropic-compatible, and native Google Gemini interfaces, making it easier to migrate existing applications and use different provider SDKs without rebuilding integrations. Its model catalog covers text generation, reasoning, coding, vision, web search, deep search, image and video generation, 3D generation, text-to-speech, speech-to-text, embeddings, reranking, structured outputs, moderation, and prompt caching. Model metadata can be filtered by type, input modality, capability, context length, coding suitability, and other properties to help teams select an appropriate option.
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    Activeloop

    Activeloop

    Activeloop

    Activeloop provides a continuous learning infrastructure for teams building software, agents, and data pipelines. Its core product, Deeplake, is the GPU database for agents, built around the idea that if your AI is on a GPU, your data should be too. Deeplake is designed to keep AI agents grounded, versioned, queryable, and GPU-native by combining vector and tensor data in one store, with GPU streaming to fine-tuning and a serverless Postgres interface. It gives teams a data engine for multimodal AI, allowing them to store, index, search, and stream data to models and agents. Instead of treating AI data as scattered files, embeddings, metadata, and traces across disconnected systems, Activeloop brings them into an infrastructure that can support retrieval, model development, fine-tuning, and agent memory workflows. It also includes Hivemind, where agent traces become team skills, so work solved once can be shared across the organization through trajectory capture.
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    Klique

    Klique

    Klique

    Klique is an enterprise AI control plane that centralizes model routing, AI service governance, and compute orchestration across on-premises, cloud, and hybrid environments. The platform routes AI requests to appropriate models based on factors such as cost, latency, policy, and data sensitivity while also directing workloads to suitable infrastructure. It provides centralized controls for budgets, quotas, virtual keys, single sign-on, audit trails, and access policies across users, agents, models, projects, and tools. Klique can manage in-house models, open-source models, third-party APIs, GPU clusters, CPUs, Kubernetes environments, and cloud AI services through a unified layer. Its orchestration capabilities support shared compute pools, fractional GPU usage, priority scheduling, training jobs, data processing, and live model deployments.
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    Axolotl

    Axolotl

    Axolotl

    ​Axolotl is an open source tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures. It enables users to train models, supporting methods like full fine-tuning, LoRA, QLoRA, ReLoRA, and GPTQ. Users can customize configurations using simple YAML files or command-line interface overrides, and load different dataset formats, including custom or pre-tokenized datasets. Axolotl integrates with technologies like xFormers, Flash Attention, Liger kernel, RoPE scaling, and multipacking, and works with single or multiple GPUs via Fully Sharded Data Parallel (FSDP) or DeepSpeed. It can be run locally or on the cloud using Docker and supports logging results and checkpoints to several platforms. It is designed to make fine-tuning AI models friendly, fast, and fun, without sacrificing functionality or scale.
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    Code Snippets AI

    Code Snippets AI

    Code Snippets AI

    Turn your questions into code. Easily store and fetch your snippets. Collaborate with your team. Powered by ChatGPT & our fine-tuned GPT3 model. Gain a deeper understanding of your code to further your knowledge. Increase the quality of your code with our refactor and debug features. Securely share code snippets with your team, without losing formatting. We use ChatGPT & our fine-tuned GPT3 Model, which provides faster and more accurate responses to your questions, compared to Codex apps. Create documentation, refactor, debug, and generate code with the click of a button. We use a fine-tuned AI model trained on GPT3, which provides faster and more accurate responses to your questions, compared to Codex apps. Save your code from your IDE straight into your library with our VSCode extension. Search snippets by language, name, or folder. Create your own folder structure to suit your needs. We use ChatGPT & our fine-tuned GPT3 Model, which provides faster and more accurate responses.
    Starting Price: $2 per month
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    Llama 2
    The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.
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    AgentKit

    AgentKit

    OpenAI

    AgentKit is a unified suite of tools designed to streamline the process of building, deploying, and optimizing AI agents. It introduces Agent Builder, a visual canvas that lets developers compose multi-agent workflows via drag-and-drop nodes, set guardrails, preview runs, and version workflows. The Connector Registry centralizes the management of data and tool integrations across workspaces and ensures governance and access control. ChatKit enables frictionless embedding of agentic chat interfaces, customizable to match branding and experience, into web or app environments. To support robust performance and reliability, AgentKit enhances its evaluation infrastructure with datasets, trace grading, automated prompt optimization, and support for third-party models. It also supports reinforcement fine-tuning to push agent capabilities further.
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    prompteasy.ai

    prompteasy.ai

    prompteasy.ai

    You can now fine-tune GPT with absolutely zero technical skills. Enhance AI models by tailoring them to your specific needs. Prompteasy.ai helps you fine-tune AI models in a matter of seconds. We make AI tailored to your needs by helping you fine-tune it. The best part is, that you don't even have to know AI fine-tuning. Our AI models will take care of everything. We will be offering prompteasy for free as part of our initial launch. We'll be rolling out pricing plans later this year. Our vision is to make AI smart and easily accessible to anyone. We believe that the true power of AI lies in how we train and orchestrate the foundational models, as opposed to just using them off the shelf. Forget generating massive datasets, just upload relevant materials and interact with our AI through natural language. We take care of building the dataset ready for fine-tuning. You just chat with the AI, download the dataset, and fine-tune GPT.
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    SiliconFlow

    SiliconFlow

    SiliconFlow

    SiliconFlow is a high-performance, developer-focused AI infrastructure platform offering a unified and scalable solution for running, fine-tuning, and deploying both language and multimodal models. It provides fast, reliable inference across open source and commercial models, thanks to blazing speed, low latency, and high throughput, with flexible options such as serverless endpoints, dedicated compute, or private cloud deployments. Platform capabilities include one-stop inference, fine-tuning pipelines, and reserved GPU access, all delivered via an OpenAI-compatible API and complete with built-in observability, monitoring, and cost-efficient smart scaling. For diffusion-based tasks, SiliconFlow offers the open source OneDiff acceleration library, while its BizyAir runtime supports scalable multimodal workloads. Designed for enterprise-grade stability, it includes features like BYOC (Bring Your Own Cloud), robust security, and real-time metrics.
    Starting Price: $0.04 per image
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    Run BiOS

    Run BiOS

    UltraSafe AI Inc.

    Run BiOS is serverless, OpenAI-compatible inference. Point the OpenAI SDK at the Run BiOS endpoint and keep your code. Six model families — Claude, DeepSeek, GLM, Kimi, MiniMax and Qwen — plus bios-adaptive, which routes each request for quality, speed and budget against a published price ceiling. Prompts and responses live in memory and are discarded when the request completes: no request logs, no content store, no archive. Fine-tuning and dedicated GPU endpoints run from the same account if you later want weights you own, billed per second of GPU time. Pricing is usage-based from a pre-paid balance, published per million tokens, and an endpoint pauses rather than running up a debt if the balance reaches zero. Start with $10 in credit, no card required.
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    Swiftask

    Swiftask

    Swiftask

    Swiftask enables organizations to orchestrate multiple AI models into automated workflows without coding, delivering enterprise governance and seamless integration. Chain AI models into end-to-end processes: automatically research leads, score opportunities, update CRM; monitor competitors, extract insights, generate reports; analyze tickets, draft responses, translate content, route to teams—transforming hours of work into minutes of automation. Build AI knowledge assistants that query HR policies, technical docs, and product specs, eliminating repetitive questions and reducing response times from hours to seconds. Business teams create agents through intuitive no-code interfaces, defining roles, connecting data, and configuring workflows to deploy in days. Enterprise control includes RBAC, complete audit logs, and SSO/SAML authentication to monitor usage, manage costs, ensure compliance, and eliminate Shadow IT.
    Starting Price: €24/month
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    SERA

    SERA

    Ai2

    Open Coding Agents are a family of fully open, high-performance AI coding models and an associated training method released by the Allen Institute for AI that make building, customizing, and training coding agents on any repository remarkably accessible, affordable, and transparent; the platform includes models, code, training recipes, and tools that can be launched with minimal setup so users can tailor agents to their own codebases and engineering conventions for tasks like code generation, code review, debugging, maintenance, and code explanation. These agents break from the traditional closed, expensive systems by offering an open pipeline from models to training data and enabling fine-tuning on internal code to teach agents about organization-specific APIs, patterns, and workflows; the first release, SERA (Soft-verified Efficient Repository Agents), achieves state-of-the-art performance on coding benchmarks at a fraction of the typical compute cost.
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    Onyx Security

    Onyx Security

    Onyx Security

    Onyx is a secure AI control plane for discovering, protecting, governing, optimizing, and measuring AI agents and models across the enterprise. It gives security, governance, and AI teams visibility into sanctioned and shadow AI across SaaS, cloud, endpoints, and code, including prompts, responses, and agent actions. AI Security helps strengthen posture, identify vulnerabilities, and enforce real-time safeguards against threats and misuse, while AI Governance supports security standards and regulatory requirements with opt-in coverage and policy controls defined in natural language. AI Orchestration reduces friction when setting up agents and MCPs and helps optimize for cost, accuracy, and latency. AI ROI measures adoption, sets goals, and tracks outcomes across departments. The Onyx Guardian Agent acts as a supervisory AI that continuously identifies risks and remediates issues across the platform, helping organizations manage large numbers of agents at scale.
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    Maetra

    Maetra

    Maetra

    Maetra is an AI governance and compliance control plane for teams operating tool-using AI agents. Discover inventories agents and capabilities; Comply maps systems to applicable frameworks and keeps reusable evidence current; Govern evaluates consequential actions against versioned policies and routes human approval when required. Secure scans prompts, messages, model outputs, and tool calls for prompt injection, data exposure, unsafe actions, and policy violations. Task Guard detects task drift, scope changes, and mismatched effects. Interaction Guard protects supported browser-AI prompts and files, while Audit preserves linked decision, approval, runtime, and change evidence. Teams can adopt modules separately or together through the web app, REST APIs, SDKs, and MCP. A 14-day no-card trial is available, with paid plans from $20/month.
    Starting Price: $20/month
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    Laguna XS.2

    Laguna XS.2

    Poolside

    Laguna XS.2 is Poolside’s open-weight agentic coding model, built as the lightest and fastest model in the Laguna family. It is a 33B total-parameter Mixture of Experts model with 3B activated parameters, trained completely in-house on 30T tokens. As Poolside’s newest generation model open to the community, Laguna XS.2 is a second-generation architecture and the company’s first open-weight model, built on the lessons learned from training Laguna M.1 across synthetic data and reinforcement learning. The model is designed for agentic coding workflows, where it can code, act, iterate quickly, and perform best inside Poolside’s coding agent. Laguna XS.2 is positioned as a strong model for rapid agentic iteration, especially for developers and teams that need a compact, efficient coding model rather than a heavier frontier system. It is released under an Apache 2.0 license, allowing the community to evaluate, fine-tune, quantize, serve, and build on the weights.
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    Lunar.dev

    Lunar.dev

    Lunar.dev

    Lunar.dev is an AI gateway and API consumption management platform that gives engineering teams a single, unified control plane to monitor, govern, secure, and optimize all outbound API and AI agent traffic, including calls to large language models, Model Context Protocol tools, and third-party services, across distributed applications and workflows. It provides real-time visibility into usage, latency, errors, and costs so teams can observe every model, API, and agent interaction live, and apply policy enforcement such as role-based access control, rate limiting, quotas, and cost guards to maintain security and compliance while preventing overuse or unexpected bills. Lunar.dev's AI Gateway centralizes control of outbound API traffic with identity-aware routing, traffic inspection, data redaction, and governance, while its MCPX gateway consolidates multiple MCP servers under one secure endpoint with full observability and permission management for AI tools.
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    Helix AI

    Helix AI

    Helix AI

    Build and optimize text and image AI for your needs, train, fine-tune, and generate from your data. We use best-in-class open source models for image and language generation and can train them in minutes thanks to LoRA fine-tuning. Click the share button to create a link to your session, or create a bot. Optionally deploy to your own fully private infrastructure. You can start chatting with open source language models and generating images with Stable Diffusion XL by creating a free account right now. Fine-tuning your model on your own text or image data is as simple as drag’n’drop, and takes 3-10 minutes. You can then chat with and generate images from those fine-tuned models straight away, all using a familiar chat interface.
    Starting Price: $20 per month
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    ReByte

    ReByte

    RealChar.ai

    Action-based orchestration to build complex backend agents with multiple steps. Working for all LLMs, build fully customized UI for your agent without writing a single line of code, serving on your domain. Track every step of your agent, literally every step, to deal with the nondeterministic nature of LLMs. Build fine-grain access control over your application, data, and agent. Specialized fine-tuned model for accelerating software development. Automatically handle concurrency, rate limiting, and more.
    Starting Price: $10 per month
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    OpenPipe

    OpenPipe

    OpenPipe

    OpenPipe provides fine-tuning for developers. Keep your datasets, models, and evaluations all in one place. Train new models with the click of a button. Automatically record LLM requests and responses. Create datasets from your captured data. Train multiple base models on the same dataset. We serve your model on our managed endpoints that scale to millions of requests. Write evaluations and compare model outputs side by side. Change a couple of lines of code, and you're good to go. Simply replace your Python or Javascript OpenAI SDK and add an OpenPipe API key. Make your data searchable with custom tags. Small specialized models cost much less to run than large multipurpose LLMs. Replace prompts with models in minutes, not weeks. Fine-tuned Mistral and Llama 2 models consistently outperform GPT-4-1106-Turbo, at a fraction of the cost. We're open-source, and so are many of the base models we use. Own your own weights when you fine-tune Mistral and Llama 2, and download them at any time.
    Starting Price: $1.20 per 1M tokens
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    LLaMA-Factory

    LLaMA-Factory

    hoshi-hiyouga

    ​LLaMA-Factory is an open source platform designed to streamline and enhance the fine-tuning process of over 100 Large Language Models (LLMs) and Vision-Language Models (VLMs). It supports various fine-tuning techniques, including Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and Prefix-Tuning, allowing users to customize models efficiently. It has demonstrated significant performance improvements; for instance, its LoRA tuning offers up to 3.7 times faster training speeds with better Rouge scores on advertising text generation tasks compared to traditional methods. LLaMA-Factory's architecture is designed for flexibility, supporting a wide range of model architectures and configurations. Users can easily integrate their datasets and utilize the platform's tools to achieve optimized fine-tuning results. Detailed documentation and diverse examples are provided to assist users in navigating the fine-tuning process effectively.
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    FinetuneDB

    FinetuneDB

    FinetuneDB

    Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance. Know exactly what goes on in production with an in-depth log overview. Collaborate with product managers, domain experts and engineers to build reliable model outputs. Track AI metrics such as speed, quality scores, and token usage. Copilot automates evaluations and model improvements for your use case. Create, manage, and optimize prompts to achieve precise and relevant interactions between users and AI models. Compare foundation models, and fine-tuned versions to improve prompt performance and save tokens. Collaborate with your team to build a proprietary fine-tuning dataset for your AI models. Build custom fine-tuning datasets to optimize model performance for specific use cases.
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    Edgee

    Edgee

    Edgee

    Edgee is an AI gateway that sits between your application and large language model providers, acting as an edge intelligence layer that compresses prompts before they reach the model to reduce token usage, lower costs, and improve latency without changing your existing code. Applications call Edgee through a single OpenAI-compatible API, and Edgee applies edge-level policies such as intelligent token compression, routing, privacy controls, retries, caching, and cost governance before forwarding requests to the selected provider, including OpenAI, Anthropic, Gemini, xAI, and Mistral. Its token compression engine removes redundant input tokens while preserving semantic intent and context, achieving up to 50% input token reduction, which is especially valuable for long contexts, RAG pipelines, and multi-turn agents. Edgee enables tagging requests with custom metadata to track usage and spending by feature, team, project, or environment, and provides cost alerts when spending spikes.
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    packet.ai

    packet.ai

    packet.ai

    packet.ai is a GPU cloud platform built to give developers and AI teams fast access to high-performance computing without the complexity and inefficiencies of traditional cloud infrastructure. It provides on-demand GPU instances, including modern NVIDIA hardware, that can be launched in seconds and accessed through tools like SSH, Jupyter, or VS Code, enabling users to quickly start training models, running inference, or experimenting with AI workloads. It introduces a different approach to GPU usage by dynamically allocating resources based on real-time workload demands, rather than treating a GPU as a fixed unit, allowing multiple compatible workloads to share hardware efficiently while maintaining predictable performance. This results in higher utilization and eliminates the need to pay for idle capacity, focusing instead on the exact compute resources consumed. packet.ai also offers an OpenAI-compatible API for language model inference, embeddings, and fine-tuning, etc.
    Starting Price: $0.39/hour
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    Smaug Flash

    Smaug Flash

    Abacus.AI

    Smaug Flash is a family of three open-weight models fine-tuned by Abacus.AI for production agentic workloads, with each model positioned at a different point on the capability–efficiency curve. The line is trained using human-curated real-world agentic traces combined with synthetic data grounded in difficult examples, producing gains in agentic coding, real-world tool use, automation, long-context reasoning, and instruction following. Smaug Flash, based on DeepSeek V4 Flash 0731, is the workhorse model for enterprise self-improving agents where speed, efficiency, and reliable agent performance need to coexist. It is specifically tuned to reduce the spins and confusion that can appear during long-context tool use while retaining the base model’s speed advantages. Smaug Mini, based on Qwen3.8 27B, targets multimodal use cases and smaller reasoning tasks in a more compact package, with stronger real-world agentic ability for one-off workflows.
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    Capriole AI

    Capriole AI

    Capriole Australia PTY LTD

    Capriole AI is an all-in-one AI workspace for unlimited web chat and unlimited image generation, with API access priced far below official provider rates. It brings leading models from OpenAI, Anthropic, Google, xAI, Z.ai, and Moonshot into one interface so users can switch models within the same conversation, choose Fast or Thinking modes, search the web, and analyze files. Privacy controls provide cloud-synced, browser-local, or No Storage chat history. Its OpenAI-compatible and Anthropic Messages APIs work with Python, Node.js, and cURL and connect one API key to Codex, Claude Code, GitHub Copilot CLI, OpenCode, OpenClaw, Kilo Code, and other coding agents. The interface supports English, Chinese, Spanish, German, Japanese, Korean, and Portuguese. Capriole AI offers a free plan, Premium from $8/month, and Team plans for five seats with shared usage and owner-managed billing.
    Starting Price: $8/month
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    SuperAGI SuperCoder
    SuperAGI SuperCoder is an open-source autonomous system that combines AI-native dev platform & AI agents to enable fully autonomous software development starting with python language & frameworks SuperCoder 2.0 leverages LLMs & Large Action Model (LAM) fine-tuned for python code generation leading to one shot or few shot python functional coding with significantly higher accuracy across SWE-bench & Codebench As an autonomous system, SuperCoder 2.0 combines software guardrails specific to development framework starting with Flask & Django with SuperAGI’s Generally Intelligent Developer Agents to deliver complex real world software systems SuperCoder 2.0 deeply integrates with existing developer stack such as Jira, Github or Gitlab, Jenkins, CSPs and QA solutions such as BrowserStack /Selenium Clouds to ensure a seamless software development experience
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    Entry Point AI

    Entry Point AI

    Entry Point AI

    Entry Point AI is the modern AI optimization platform for proprietary and open source language models. Manage prompts, fine-tunes, and evals all in one place. When you reach the limits of prompt engineering, it’s time to fine-tune a model, and we make it easy. Fine-tuning is showing a model how to behave, not telling. It works together with prompt engineering and retrieval-augmented generation (RAG) to leverage the full potential of AI models. Fine-tuning can help you to get better quality from your prompts. Think of it like an upgrade to few-shot learning that bakes the examples into the model itself. For simpler tasks, you can train a lighter model to perform at or above the level of a higher-quality model, greatly reducing latency and cost. Train your model not to respond in certain ways to users, for safety, to protect your brand, and to get the formatting right. Cover edge cases and steer model behavior by adding examples to your dataset.
    Starting Price: $49 per month
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    AICtrlNet

    AICtrlNet

    Bodaty LLC

    AICtrlNet enforces AI governance instead of only observing it. Unlike tools that score or monitor AI risk, it runs the work — orchestrating AI agents, humans (as first-class agents, not just approval gates), and enterprise systems under a unified governance model. Model-independent across OpenAI, Claude, Gemini, and local runtimes (Ollama, vLLM). A 6-phase Control Spectrum sets autonomy per workflow and agent. Ships 43 role-configured agent templates and 177+ workflow templates across 41 industry packs. Runs n8n, Zapier, and Make as nodes rather than replacing them. Supports HIPAA, GDPR, SOC2, and EU AI Act via design-time governance and audit-grade accountability. Open-core editions: Community (MIT, free, self-hostable) ships the core platform; Business adds ML-enhanced governance and risk scoring; Enterprise adds multi-tenancy and federation. Access via the HitLai visual no-code interface, REST API, or MCP.
    Starting Price: $599/month
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    Lens

    Lens

    Moondream

    Lens is Moondream’s official fine-tuning service, designed to turn a general vision-language model into a highly specialized system tailored to a specific task. It provides a simple, structured workflow where users start by collecting a small dataset of images relevant to their use case, then fine-tune the model through an API using techniques such as supervised fine-tuning (SFT) or reinforcement learning, and finally deploy the customized model either through the cloud or locally with Photon. It is built around the idea that Moondream begins as a general model trained on broad, public data, and fine-tuning adapts it to understand the exact products, documents, categories, or internal information that matter to a business, significantly improving accuracy and reliability for that domain. Lens is designed for production scenarios where performance matters, enabling teams to achieve large gains in accuracy with minimal data by teaching the model to master a defined task.
    Starting Price: $300 per month
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    Enkrypt AI

    Enkrypt AI

    Enkrypt AI

    Enkrypt AI is an enterprise AI security, compliance, and governance platform purpose-built to secure LLMs, AI agents, multimodal systems, and MCP workflows. Serving enterprises in finance, healthcare, insurance, and government, Enkrypt AI helps organizations ship fast, ship safe, and stay ahead. The platform covers the full AI security lifecycle: Guardrails: Ultra-low latency (sub-50ms) policy-based guardrails prevent prompt injection, sensitive data exposure, unsafe outputs, and non-compliant agent behavior in real time. Red Teaming: Policy-driven, multimodal attack simulation across LLMs and AI agents before deployment. MCP Security: MCP Scan Hub and Secure MCP Gateway protect MCP servers, tools, and agent toolchains end-to-end. Compliance: Continuous monitoring against NIST AI RMF, OWASP LLM Top 10, EU AI Act, HIPAA, and FINRA. ISO 27001 & SOC 2 Type II certified. Gartner Cool Vendor 2025.
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    CyCraft XecGuard
    XecGuard is CyCraft’s LLM Firewall for trustworthy, agentic AI, designed to protect enterprise AI systems from prompt injection, jailbreak, prompt extraction, data leakage, unsafe outputs, and agentic workflow risks. Built on CyCraft’s red teaming and blue teaming experience across government, finance, and high-tech manufacturing, XecGuard goes beyond model-level defenses by combining AI guardrails, cybersecurity controls, compliance protection, and risk response strategies for real-world enterprise AI adoption. It is positioned as a plug-and-play LoRA security module that can strengthen LLM defenses without requiring changes to the underlying model architecture, helping teams add protection quickly while preserving performance. XecGuard is built on proprietary security datasets and multi-stage fine-tuning techniques, enabling LLMs to better resist adversarial prompts, malicious manipulation, and attempts to extract protected instructions or sensitive information.