Alternatives to Sage2
Compare Sage2 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Sage2 in 2026. Compare features, ratings, user reviews, pricing, and more from Sage2 competitors and alternatives in order to make an informed decision for your business.
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Sage Intacct
Sage Intacct
Sage Intacct is a premier cloud-based financial management software designed for growing businesses. It offers comprehensive features including core financials, accounts payable and receivable, cash management, and multi-entity consolidations. Sage Intacct's advanced modules cater to complex financial needs, ensuring scalability as your business grows. The software integrates seamlessly with other business applications, providing real-time financial and operational insights. Its user-friendly interface and customizable dashboards empower your team to adapt quickly and make data-driven decisions. Sage Intacct's robust reporting capabilities and automation of key financial processes help improve accuracy, efficiency, and compliance. Trusted by thousands of organizations, Sage Intacct streamlines financial operations, enhances visibility, and drives business growth. With award-winning customer support and continuous innovation, Sage Intacct is your partner. -
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Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
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SubQ Snap 1.1
Subquadratic
SubQ Snap is a hosted multimodal decision model for developers building AI agents and enterprise workflows. Through Subquadratic’s API, applications send text or image context with defined questions and receive structured answers such as labels, choices, scores, and probabilities. This supports tasks including tool and file selection, routing, triage, guardrails, ranking, classification, and checking whether a test or result meets specified criteria. The model accepts up to 384K tokens of context and supports image input. It is designed for bounded decisions rather than open-ended text generation, so it can be used alongside a language model that handles planning or writing. Public-preview API documentation includes request examples, model access details, and decision formats.Starting Price: $0.05/1M input tokens -
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Parallel Decisions API
Parallel
Parallel Decisions API is a hosted, web-grounded classification API for developers building software, data-enrichment pipelines, and AI-agent workflows. A request supplies context and one or more bounded questions; the API returns typed answers with probabilities and citations to supporting web sources. Multiple questions can share context in a single request, supporting uses such as company or vendor qualification, lead routing, compliance screening, content filtering, and agent guardrails. By retrieving current web evidence, it can assess facts that may have changed since a model's training data. Developers call the REST endpoint with an API key or access the web_decisions tool through Parallel's MCP server. A hosted playground and documentation support testing and implementation.Starting Price: $0.001/request -
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Jev
TypeSafe AI
Jev is a System One Model from TypeSafe AI designed for fast, structured decision-making inside software and automated workflows. Unlike conventional large language models that generate free-form text token by token, Jev accepts unstructured state and returns predefined type-safe values with calibrated probabilities and confidence scores. The model uses a parallel sampling architecture and a training approach called Reinforcement Learning for Calibrated Decisions, which is optimized for producing reliable probabilistic decisions rather than conversational responses. Jev is intended for tasks such as classification, routing, scoring, extraction, branching logic, verification, guardrails, and other AI-powered workflows where structured outputs can plug directly into application code. TypeSafe reports end-to-end response times ranging from about 70 to 500 milliseconds and says Jev can be substantially faster and more efficient than frontier language models on System One-style workloads.Starting Price: Input: $0.042 / 1M tokens -
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Gemini Decision 1
Google
Gemini Decision 1 is an artificial intelligence decision-making model developed by Google for classification, routing, scoring, and structured evaluation tasks. Unlike traditional generative AI models that produce conversational responses, Gemini Decision 1 analyzes input information and returns structured decisions with associated probabilities and confidence values. The model supports Boolean questions, multiple-choice selections, and numerical or ordinal scoring to help applications make automated decisions. It can process large amounts of contextual information using a context window of approximately 262,000 tokens. Developers can integrate the model into applications for content categorization, customer support triage, workflow automation, and AI agent decision-making. Available through API integrations, Gemini Decision 1 helps organizations build intelligent systems that evaluate information and produce measurable, structured outputs.Starting Price: $0.10 per 1M tokens (input) -
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Microsoft-Decision-1
Microsoft
Microsoft-Decision-1 is a fast decision-scoring model built for structured outputs that software can immediately act on. It is designed for routing, classification, prioritization, verification, and workflow control across applications, agents, and automated systems. The model is post-trained from Qwen3.5-9B for single-pass decision scoring and, when given a fixed set of answer options, returns a calibrated probability for each one. It supports yes/no, multiple-choice, rating, and rubric-based grading of AI responses and agent actions through a structured API. Microsoft evaluated the model across 36 benchmarks covering routing, ranking, long context, multilingual and out-of-distribution tasks, reasoning, and safety, and reports that it achieved the highest accuracy in that comparison while also delivering very low latency. The model is also designed for robustness, with testing focused on keeping decisions stable when prompts are paraphrased.Starting Price: $0.042 per 1M tokens -
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Tev1
Together AI
Tev1 is a fast decision and classification model built by Together AI and fine-tuned from Qwen3.5 4B. It is designed around a simple interface: provide a piece of state, a question, and 2 to 24 labeled options, and the model returns exactly one letter that software can map back to a semantic key. This structure supports production tasks such as routing support tickets, evaluating automated returns, applying policy rules, rating sentiment, categorizing documents, and inserting deterministic decision points into larger agent pipelines. The model has 4.7B parameters, a 32.8K-token context window, and runs with non-thinking generation for fast, predictable classification. It was trained on 37,840 examples spanning intent detection, boolean comprehension, sentiment, policy application, routing, news categories, and research-paper taxonomy. Recommended settings use temperature 0 and a very small output budget so responses remain stable and easy to parse.Starting Price: $0.04 per 1M tokens -
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Laya AI
Laya AI
Laya AI is an open source family of non-autoregressive System 1 decision models built for fast, typed decisions instead of free-form text generation. Given a state and structured questions, Laya evaluates them in a single forward pass and returns outputs that application code can use directly. It supports three decision types: choice, which selects among named options and returns probabilities; score, which places an input on an ordered rubric such as urgency or severity; and noul, which estimates the probability that a proposition is true. Laya is designed for workloads such as agent and model routing, support ticket triage, guardrails, intent classification, risk and fraud scoring, workflow escalation, RAG filtering, moderation, and phishing detection. It can route requests by department, score urgency, flag refund or churn signals, detect policy or abuse conditions, and escalate uncertain cases to a larger model or human reviewer.Starting Price: Free -
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Hume Audio Decisions API
Hume AI
Hume Audio Decisions API is a hosted API for developers building voice applications and teams evaluating speech and sound. It accepts an audio recording, optional context, and user-defined questions, then returns probabilities for answers in structured form. Questions can cover observable audio facts, such as the number of speakers or background speech, and listener judgments about tone, naturalness, empathy, clarity, or frustration. Teams can use the results to review support calls, test voice agents and text-to-speech output, label speech corpora, compare recordings, and identify examples for escalation or model training. The API works as a decision layer alongside speech recognition and voice generation, allowing application code to use its scores and probabilities in custom workflows. API access is requested through Hume, and billing is based on audio, question, and context input tokens.Starting Price: $0.47/1M tokens -
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Strands Decider
Strands Labs
Strands Decider is a small, fast decision model, or System One model, built for agentic AI workflows. Unlike an LLM that generates arbitrary text, it chooses between predefined options, answers yes-or-no questions, or rates inputs on an ordered scale. Each decision includes calibrated confidence, making it possible to send uncertain cases to a larger model or a human while handling routine decisions quickly. The first model in the family, strands-decider-2B, has 1.9 billion parameters and is based on a Qwen3.5-2B-Base torso with its language-modeling head replaced by a lightweight pointer head. It evaluates answers in one forward pass without text generation or a decoding loop. Supported decision types include choice, noul for probability-of-true questions, and score for ordered scales. The model is designed for tasks such as model routing, tool selection, tool-argument checking, request triage, grounding and safety guardrails, policy classification, and low-cost evaluation.Starting Price: Free -
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Perplexity Decider
Perplexity
Perplexity Decider is a 27B decision model fine-tuned from Qwen3.8-27B for structured classification and multimodal decision tasks. Rather than generating unrestricted text, it takes an input state and a typed decision schema, then returns the selected result together with calibrated probabilities. The model supports choice decisions for selecting among predefined categories and noul decisions for estimating the probability of a yes-or-no condition. It can also accept images alongside text, allowing applications to make decisions from screenshots or other visual inputs. Example workflows include routing a support request to billing, technical support, or sales, and estimating whether a message expresses urgency. Perplexity reports an overall accuracy of 85.71% across 11 benchmarks, including FinancialPhraseBank, RAGTruth, JudgeBench, TabFact, ContractNLI, Circa, Belebele, and TruthfulQA binary.Starting Price: Free -
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Clef
Cloudflare
Clef is a 27B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and return a probability for every allowed option of every question. The model supports a 65,536-token context window and vision inputs, allowing developers to evaluate both structured application data and visual content in the same decision workflow. Clef supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options and returning per-option probabilities, and score for evaluating an input against ordered criteria and producing a probability-weighted score. Applications can submit between 1 and 64 questions in a single request, with answers returned under the same question IDs. -
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Solar Decide
Upstage
Solar Decide is Upstage’s structured decision model, serving as a System One endpoint on Solar Mini 4. Instead of generating prose, it takes a state together with one or more typed questions and returns a choice, score, or yes/no answer with calibrated probabilities taken directly from the model. Each question is handled in a single forward pass, making the model suited to fast classification, routing, policy checks, prioritization, and other structured decision tasks. The choice type selects among predefined options and returns the selected option, individual probabilities, and confidence. The score type evaluates an input against ordered criteria and returns a probability-weighted score, legend, probability distribution, and confidence. The noul type returns the probability that a yes-or-no proposition is true. Multiple questions can share the same state in one request, and the state can be provided as text or any JSON value serialized into the prompt.Starting Price: $0.1 per 1M tokens -
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Clef-flash
Cloudflare
Clef-flash is a fast 9B multimodal decision model that turns a state and a schema of typed questions into structured decisions. It can read state information as text, JSON, images, or video and returns a probability for every allowed option of every question. The model supports a 24,576-token context window and vision input, allowing developers to evaluate structured application data and visual content within the same workflow. Clef Flash supports three typed question formats: noul for estimating the probability that a proposition is true, choice for selecting among predefined options with per-option probabilities, and score for evaluating an input against ordered criteria and returning a probability-weighted score. Applications can submit from 1 to 64 questions in a single request, with answers returned under the same question IDs. Example uses include deciding whether a support request is urgent, routing it to the correct team, and scoring the severity of customer impact. -
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SubQ Snap
Subquadratic
SubQ Snap is a long-context decision model for enterprise and agentic workflows, built to make structured decisions quickly over large amounts of information. It handles tasks such as choosing which files are relevant, selecting the next tool, checking whether a result passes, deciding whether a workflow should continue, and determining when a frontier model is needed. Instead of generating open-ended text, Snap takes context, a question, and a finite set of allowed answers, then returns a probability distribution over those answers. It supports up to 384K tokens of mixed text and image context, allowing it to reason over codebases, contracts, interaction histories, logs, screenshots, charts, diagrams, and scanned pages in a single call. Powered by Subquadratic Sparse Attention, Snap reduces the cost of reading long inputs while a decision head maps contextual representations directly to admissible answers without autoregressive generation.Starting Price: $0.05 per million input tokens -
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Liquid d1
Liquid AI
d1 is Liquid AI’s first decision model, built to answer structured questions about a situation with probabilities rather than generating text. It takes unstructured data such as text, images, or both, along with one or more questions, processes them in a single forward pass, and returns probabilities without generating output tokens. d1 supports three question types: noul for yes-or-no decisions, choice for selecting among labels with a probability for each option, and score for placing an input on an ordered scale using probability-weighted levels. Multiple questions can be evaluated against the same state in one request, making it useful for real-time decision workflows. Liquid AI demonstrates d1 across applications such as filtering support tickets, browsing code repositories, organizing documents into smart folders, operating websites, compacting agent context, inspecting industrial parts, and playing games from screenshots.Starting Price: Free -
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Span-01
Respan
Span-01 is a hyper-parallel reasoning classifier built to detect complex behaviors across long production traces in a single forward pass. Rather than generating tokens sequentially, it reasons over natural-language behavior definitions and returns direct probabilities for present, absent, and not_observable. The model is trained for general classification reasoning with RLAIF before being specialized for behavior detection, allowing it to apply previously unseen definitions to new behaviors and domains instead of relying on a fixed taxonomy. At inference time, hyper-parallel definition branches evaluate multiple behaviors against the same trace context simultaneously, while hybrid attention helps preserve reasoning over long, complex inputs. Span-01 is designed for production monitoring across safety, reliability, grounding, agent behavior, and response quality, including jailbreak and prompt injection detection, privacy, and secrets.Starting Price: $199 per month -
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OpenAI Decisions API
OpenAI
The Decisions API turns text and images into typed decisions an application can use, evaluating inputs about 10x faster than the Responses API. Developers provide a model, shared input evidence, and one or more questions describing what should be evaluated, and the API returns structured answers that can be used to classify content, route requests, prioritize work, or make threshold-based decisions. It supports three question types: predicate checks whether a condition is true and returns a probability from 0 to 1; choice selects one value from a fixed set and returns option probabilities and confidence; and score evaluates an input against ordered rubric levels and returns a probability-weighted score. Inputs can be plain text or user messages containing both text and images, allowing applications to evaluate cases such as visible product damage, request intent, document type, issue severity, or answer relevance. -
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Perplexity Decisions API
Perplexity
Perplexity’s Decisions API is built for fast, structured decisions that software can use directly. Instead of generating free-form text, it reads natural-language text, JSON, or images as shared state and returns typed answers with probabilities. Developers can attach one or more named questions to the same input and choose among three question types. noul handles yes-or-no judgments and returns the probability of yes from 0 to 1. choice selects from developer-defined options and returns the most likely option, the probability of every option, and a confidence score. score evaluates content against an ordered rubric and returns a probability-weighted score, the full probability distribution, and confidence. The API is designed for tasks such as classification, routing, grading against a rubric, severity assessment, sentiment analysis, or any decision that can be compared against a threshold. -
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Amazon SageMaker Autopilot
Amazon
Amazon SageMaker Autopilot eliminates the heavy lifting of building ML models. You simply provide a tabular dataset and select the target column to predict, and SageMaker Autopilot will automatically explore different solutions to find the best model. You then can directly deploy the model to production with just one click or iterate on the recommended solutions to further improve the model quality. You can use Amazon SageMaker Autopilot even when you have missing data. SageMaker Autopilot automatically fills in the missing data, provides statistical insights about columns in your dataset, and automatically extracts information from non-numeric columns, such as date and time information from timestamps. -
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VibeAgent
Global Agent Studio
VibeAgent is a cloud-based visual builder for creating and deploying AI agents and automated workflows. Developers, founders, and teams can map workflows on a drag-and-drop canvas, configure agent roles and model settings, and connect triggers, decision logic, tools, and knowledge sources. Workflows can start from schedules, webhooks, form submissions, chat, or other events, then coordinate multi-step actions across connected services. The platform supports models including GPT-4, Claude, Gemini, and open-source models, and can use document-based knowledge sources. Users can deploy agents and monitor performance through analytics dashboards. VibeAgent is intended for teams that want to prototype and operate tool-using agents without building the workflow infrastructure from scratch; available connectors, model access, execution limits, and other features may vary by plan.Starting Price: $0 -
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BetterToken
BetterToken
BetterToken is a hosted LLM API gateway that provides API access to models from providers including Anthropic, OpenAI, Moonshot, Z.ai, DeepSeek, Alibaba Cloud and MiniMax through BetterToken account keys. It offers OpenAI-compatible and Anthropic-compatible endpoints, with a Responses-compatible setup for Codex, and lets developers connect coding tools, applications, agents and automation workflows using a custom base URL. Users can choose models from a live catalog, view token usage and request charges in the workspace, and pay through prepaid balance or monthly quota plans. Model costs vary by input, output and supported cached or media tokens. Setup guides cover tools such as Claude Code, Codex, Cursor, Dify and n8n. BetterToken is intended for developers and teams integrating hosted language models into software and automated workflows.Starting Price: $19/month -
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OmniaKey
OmniaKey
OmniaKey is a hosted AI API gateway for developers and teams building applications, coding agents, and media workflows. One account and prepaid balance provide access to language, image, video, and music models from multiple providers. For chat, clients can use OpenAI-compatible, Anthropic-native, or Gemini-native API surfaces; media generation uses asynchronous tasks with submission and result polling. The service includes model discovery, API documentation, key and usage management, and setup guides for Claude Code, Cursor, Codex CLI, Cline, and aider, plus OpenAI-compatible SDK clients. A browser-based Studio offers interactive text, image, video, and audio generators. Usage charges vary by model and billing unit and are deducted from prepaid funds; there is no monthly subscription. OmniaKey enables software and agent workflows to access multiple AI models through one account.Starting Price: $0.019/request -
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ApiGo
ApiGo
ApiGo is a hosted AI model gateway for developers and teams building applications with language models. It provides a unified API endpoint for sending requests to supported model providers, with OpenAI-compatible request formats and model selection through a shared interface. The service includes model routing and fallback configuration, API key management, request and usage logs, per-model token pricing, workspace balance controls, and dashboards for reviewing consumption. Developers can use documented setup guides to connect coding assistants and agent tools such as Cursor, Claude Code, Codex CLI, OpenCode, Kimi Code, and OpenClaw. ApiGo is intended for teams that want to manage model-provider access, usage, and billing through one hosted gateway rather than configure each provider separately.Starting Price: $0.10/1M input tokens -
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Amazon SageMaker JumpStart
Amazon
Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can access built-in algorithms with pretrained models from model hubs, pretrained foundation models to help you perform tasks such as article summarization and image generation, and prebuilt solutions to solve common use cases. In addition, you can share ML artifacts, including ML models and notebooks, within your organization to accelerate ML model building and deployment. SageMaker JumpStart provides hundreds of built-in algorithms with pretrained models from model hubs, including TensorFlow Hub, PyTorch Hub, HuggingFace, and MxNet GluonCV. You can also access built-in algorithms using the SageMaker Python SDK. Built-in algorithms cover common ML tasks, such as data classifications (image, text, tabular) and sentiment analysis. -
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Revana
Revana
Revana is a hosted API platform for generating video, images and music from application code and compatible AI clients. It provides a unified REST interface to multiple generative models, with model selection, asynchronous job handling and usage-based billing. Developers can submit generation requests through the API or connect supported MCP clients such as Claude, Claude Code and Cursor. The service also provides SDK examples and workflow guidance for developer environments. Revana is intended for developers and teams building AI-enabled applications, creative tools and automated media-production workflows that need to use different generation models through one integration. Available models, capabilities and per-generation rates vary; eligible requests may be routed among providers, and failed generations are not billed.Starting Price: $10 one-time -
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Amazon SageMaker Clarify
Amazon
Amazon SageMaker Clarify provides machine learning (ML) developers with purpose-built tools to gain greater insights into their ML training data and models. SageMaker Clarify detects and measures potential bias using a variety of metrics so that ML developers can address potential bias and explain model predictions. SageMaker Clarify can detect potential bias during data preparation, after model training, and in your deployed model. For instance, you can check for bias related to age in your dataset or in your trained model and receive a detailed report that quantifies different types of potential bias. SageMaker Clarify also includes feature importance scores that help you explain how your model makes predictions and produces explainability reports in bulk or real time through online explainability. You can use these reports to support customer or internal presentations or to identify potential issues with your model. -
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APMix
Nomvel
APMix is a hosted AI API gateway for developers who want to access multiple language-model providers through one account, API key and billing plan. It offers a catalog of models from multiple providers, with availability determined by plan. The service exposes OpenAI-compatible Chat Completions and Responses endpoints and an Anthropic-compatible Messages endpoint, allowing compatible applications and coding agents to connect by configuring a base URL and API key. Users can create keys, select models, review usage, and apply shared monthly weighted-token allowances across models. Documented setup guides cover clients including Claude Code, Codex CLI, Cursor, OpenCode and Kilo Code, plus other listed tools and SDKs. APMix is designed for software developers and teams building or operating applications and agent workflows that use hosted generative AI models.Starting Price: $4.99/month -
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Amazon SageMaker provides all the tools and libraries you need to build ML models, the process of iteratively trying different algorithms and evaluating their accuracy to find the best one for your use case. In Amazon SageMaker you can pick different algorithms, including over 15 that are built-in and optimized for SageMaker, and use over 150 pre-built models from popular model zoos available with a few clicks. SageMaker also offers a variety of model-building tools including Amazon SageMaker Studio Notebooks and RStudio where you can run ML models on a small scale to see results and view reports on their performance so you can come up with high-quality working prototypes. Amazon SageMaker Studio Notebooks help you build ML models faster and collaborate with your team. Amazon SageMaker Studio notebooks provide one-click Jupyter notebooks that you can start working within seconds. Amazon SageMaker also enables one-click sharing of notebooks.
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HostAiHub
HostAiHub LTD
HostAiHub is a managed hosting service for private instances of OpenClaw, Hermes, and n8n. Customers select an agent or workflow platform and deploy it in an isolated container with dedicated storage and an SSL-secured subdomain, without configuring servers themselves. A browser dashboard provides instance controls, while the service handles provisioning, updates, monitoring, and scheduled backups. Users can connect their own model-provider keys, with documented options including Anthropic, OpenAI, OpenRouter, DeepSeek, and Gemini; model usage is billed separately by the provider. HostAiHub also offers an OpenAI-compatible API service. Monthly, annual, and lifetime hosting plans are available, with prices varying by hosted platform and plan. The service is intended for founders, developers, agencies, and small teams that want to operate always-on AI agents or automated workflows without maintaining hosting infrastructure.Starting Price: $7/month -
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Amazon SageMaker Studio
Amazon
Amazon SageMaker Studio is an integrated development environment (IDE) that provides a single web-based visual interface where you can access purpose-built tools to perform all machine learning (ML) development steps, from preparing data to building, training, and deploying your ML models, improving data science team productivity by up to 10x. You can quickly upload data, create new notebooks, train and tune models, move back and forth between steps to adjust experiments, collaborate seamlessly within your organization, and deploy models to production without leaving SageMaker Studio. Perform all ML development steps, from preparing raw data to deploying and monitoring ML models, with access to the most comprehensive set of tools in a single web-based visual interface. Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. -
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Amazon SageMaker Unified Studio is a comprehensive, AI and data development environment designed to streamline workflows and simplify the process of building and deploying machine learning models. Built on Amazon DataZone, it integrates various AWS analytics and AI/ML services, such as Amazon EMR, AWS Glue, and Amazon Bedrock, into a single platform. Users can discover, access, and process data from various sources like Amazon S3 and Redshift, and develop generative AI applications. With tools for model development, governance, MLOps, and AI customization, SageMaker Unified Studio provides an efficient, secure, and collaborative environment for data teams.
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CaptchaNo
DishIs Technologies
CaptchaNo is a hosted API service for resolving CAPTCHA and selected anti-bot challenges in authorized software workflows. Applications send requests to the service and receive machine-readable results, such as a token, cookie, or recognized image text. It covers reCAPTCHA variants, Cloudflare Turnstile, DataDome, and image/text challenges through one REST interface, with account usage reporting and billing for successful solves. Developers can connect it to QA and test automation, AI-agent workflows, and data-collection systems they are permitted to access; documentation includes examples for Selenium, Puppeteer, Playwright, Scrapy, n8n, and MCP-compatible agents. Pricing includes prepaid pay-as-you-go credits and monthly volume plans, and new accounts receive a limited free trial. CaptchaNo is intended for systems customers own or are authorized to test or access.Starting Price: $1.50/1,000 solves -
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Amazon SageMaker Pipelines
Amazon
Using Amazon SageMaker Pipelines, you can create ML workflows with an easy-to-use Python SDK, and then visualize and manage your workflow using Amazon SageMaker Studio. You can be more efficient and scale faster by storing and reusing the workflow steps you create in SageMaker Pipelines. You can also get started quickly with built-in templates to build, test, register, and deploy models so you can get started with CI/CD in your ML environment quickly. Many customers have hundreds of workflows, each with a different version of the same model. With the SageMaker Pipelines model registry, you can track these versions in a central repository where it is easy to choose the right model for deployment based on your business requirements. You can use SageMaker Studio to browse and discover models, or you can access them through the SageMaker Python SDK. -
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Amazon SageMaker Edge
Amazon
The SageMaker Edge Agent allows you to capture data and metadata based on triggers that you set so that you can retrain your existing models with real-world data or build new models. Additionally, this data can be used to conduct your own analysis, such as model drift analysis. We offer three options for deployment. GGv2 (~ size 100MB) is a fully integrated AWS IoT deployment mechanism. For those customers with a limited device capacity, we have a smaller built-in deployment mechanism within SageMaker Edge. For customers who have a preferred deployment mechanism, we support third party mechanisms that can be plugged into our user flow. Amazon SageMaker Edge Manager provides a dashboard so you can understand the performance of models running on each device across your fleet. The dashboard helps you visually understand overall fleet health and identify the problematic models through a dashboard in the console. -
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GPT-5.1-Codex
OpenAI
GPT-5.1-Codex is a specialized version of the GPT-5.1 model built for software engineering and agentic coding workflows. It is optimized for both interactive development sessions and long-horizon, autonomous execution of complex engineering tasks, such as building projects from scratch, developing features, debugging, performing large-scale refactoring, and code review. It supports tool-use, integrates naturally with developer environments, and adapts reasoning effort dynamically, moving quickly on simple tasks while spending more time on deep ones. The model is described as producing cleaner and higher-quality code outputs compared to general models, with closer adherence to developer instructions and fewer hallucinations. GPT-5.1-Codex is available via the Responses API route (rather than a standard chat API) and comes in variants including “mini” for cost-sensitive usage and “max” for the highest capability.Starting Price: $1.25 per input -
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boldrouter
Cybrient Technologies
boldrouter is a hosted AI gateway for developers and teams building applications with large language models. It provides an OpenAI-compatible API and a unified endpoint for routing requests across model providers, with automatic selection and failover based on price, latency, or provider health. Teams can use prepaid credits or connect their own provider keys, manage API keys and spending limits, and review token, model, and latency usage in a dashboard. Additional capabilities include streaming, tool calls, multimodal requests, embeddings, document text extraction, model consensus and evaluation, and optional prompt anonymization that redacts personal data before forwarding requests. The Swiss-hosted service supports application, SaaS, agent, and developer-tool workflows that need access to multiple AI models.Starting Price: 5.5% per top-up -
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Tikway
Tikway
Tikway is a hosted AI model gateway and API for developers building applications that use multiple model providers. It provides a unified API key and supports request formats compatible with OpenAI, Anthropic, and Gemini protocols, allowing clients to call listed models through Tikway. Developers can browse the model catalog to compare model pricing, capabilities, and supported parameters, and use online documentation for setup and request examples. The service uses usage-based billing, with charges varying by the selected model and usage. Tikway is intended for independent developers, makers, and teams integrating generative AI into applications. Model availability, capabilities, and supported parameters vary by model; developers can consult the catalog before choosing an endpoint. -
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MISys Manufacturing
MISys, Inc.
MISys Manufacturing is a reliable manufacturing software solution available on both hosted-cloud and on-premise platforms. This purpose-built solution is specifically designed for small to midsize manufacturing businesses, and is simple to install, quick to implement, and easy to use. With MISys Manufacturing, you can reduce inventory costs, eliminate purchasing errors, improve production efficiency, and analyze production costs with greater accuracy. This solution also offers low cost of ownership and flexibility in a modular design, with advanced capabilities such as production & purchasing management, forecasting, material requirements planning (MRP), WIP, labor tracking, serial/lot tracking, barcoding and more. Plus, MISys Manufacturing seamlessly integrates with popular accounting applications like QuickBooks Desktop and Online, Sage 50, Sage 50 Canada, Sage 300, and Sage Intacct. Streamline your operations with MISys Manufacturing - learn more at misysinc.com.Starting Price: $150/month paid annually -
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DemoGPT
Melih Ünsal
DemoGPT is an open source platform that simplifies the creation of LLM (Large Language Model) agents by providing an all-in-one toolkit. It offers tools, frameworks, prompts, and models for rapid agent development. The platform automatically generates LangChain code, which can be used for creating interactive applications with Streamlit. DemoGPT translates user instructions into functional applications through a multi-step process: planning, task creation, and code generation. It supports a streamlined approach to building AI-powered agents, offering an accessible environment for developing sophisticated, production-ready solutions with GPT-3.5-turbo. Additionally, it integrates API usage and external API interaction in future updates.Starting Price: Free -
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octomind
Muvon
octomind is an open-source runtime for building and running AI agents from a local command-line environment. It includes an agent engine, connections to major language-model providers, configurable skills and tools, and a runtime server for clients that interact with agents. Developers can use it for coding, research, workflow automation, and other tool-using tasks, with support for Windows, macOS, and Linux. The runtime supports more than 20 model providers, Model Context Protocol (MCP) tools, and event-driven workflows that respond to activity from services such as GitHub, Slack, and PagerDuty. octomind is distributed under the Apache 2.0 license; model-provider accounts or API usage may incur separate charges. -
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asklog
asklog
asklog is a desktop and mobile companion for developers who run Claude Code or Codex on their own computers. It brings sessions from connected machines into one workspace, so developers can follow agent output, answer prompts, and resume work remotely from a phone or another computer while the host machine remains online. Its Chief feature can delegate coding tasks to multiple agents in separate working copies, track their progress, and return results and decisions to the developer for review. asklog uses developers’ existing agent accounts rather than providing its own coding model. The product offers applications for Windows, macOS, Linux, iPhone, and Android, along with a browser-based workspace. It is designed for developers and teams coordinating coding-agent sessions, reviewing concurrent work, and tracking tasks across devices. Separate working copies are not security sandboxes.Starting Price: ₹849/month -
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Amazon SageMaker Model Training reduces the time and cost to train and tune machine learning (ML) models at scale without the need to manage infrastructure. You can take advantage of the highest-performing ML compute infrastructure currently available, and SageMaker can automatically scale infrastructure up or down, from one to thousands of GPUs. Since you pay only for what you use, you can manage your training costs more effectively. To train deep learning models faster, SageMaker distributed training libraries can automatically split large models and training datasets across AWS GPU instances, or you can use third-party libraries, such as DeepSpeed, Horovod, or Megatron. Efficiently manage system resources with a wide choice of GPUs and CPUs including P4d.24xl instances, which are the fastest training instances currently available in the cloud. Specify the location of data, indicate the type of SageMaker instances, and get started with a single click.
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Amazon SageMaker Ground Truth
Amazon Web Services
Amazon SageMaker allows you to identify raw data such as images, text files, and videos; add informative labels and generate labeled synthetic data to create high-quality training data sets for your machine learning (ML) models. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which give you the flexibility to use an expert workforce to create and manage data labeling workflows on your behalf or manage your own data labeling workflows. data labeling. If you want the flexibility to create and manage your own personal and data labeling workflows, you can use SageMaker Ground Truth. SageMaker Ground Truth is a data labeling service that makes data labeling easy and gives you the option of using human annotators via Amazon Mechanical Turk, third-party providers, or your own private staff.Starting Price: $0.08 per month -
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LunaRoute
LunaRoute
LunaRoute is a hosted AI inference gateway and API for developers and teams running coding agents, personal agents, applications, and automations. It routes requests to a curated catalog of open-weight models through OpenAI-compatible and Anthropic-compatible endpoints, with a command-line client and setup guides for connecting coding tools and agent frameworks. Plans provide priority concurrent inference capacity, overflow handling, model access, API keys, usage reporting, and team controls depending on the plan. An optional hosted MCP server provides web search, document conversion with OCR, and image generation and editing. Enterprise offerings add dedicated deployment options, custom routing, and policy controls. LunaRoute is intended for software developers and engineering teams seeking a managed way to connect existing AI clients to model inference.Starting Price: $19.99/month -
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SAGE
HolistiCyber
SAGE, an AI-driven, cyber defense platform, supports the CISOs mission to build and operate an effective and efficient cyber defense plan. It keeps the defense plan relevant and dynamic, automatically ingesting all reports and assessments by various vendors, and its AI connects and analyzes the variables in the defense plan. SAGE is purpose-built for CISOs. It considers the needs of the organization: business impact analysis, risk tolerance, cyber posture, attack surface, etc., then considers attack vectors and analyzes everything with HolistiCyber’s unique methods in seeing the attack surface the way an attacker would. SAGE includes a context map of everything that matters – risks, vulnerabilities, assets, cyber threats, and how they impact the business. The platform provides simple presentation options for management, translating cyber risks into business risks, and includes “what-if” analysis to optimize budget usage for cyber security. -
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LFM3
Liquid AI
LFM3 is Liquid AI’s family of compact, open-weight foundation models for text, vision, audio, and multimodal tasks. The release includes text-generation, vision-language, audio, omni, and decision-model variants. Developers can download the model weights, adapt supported models through fine-tuning, and run them locally on edge hardware or access them through Liquid AI’s hosted API. Use cases include conversational assistants, tool calling, speech transcription and generation, image and video understanding, document extraction, classification, routing, and robotics applications. LFM3 is intended for developers, researchers, and organizations building specialized AI applications that need flexible deployment choices, including local inference. Open-weight models are available under Liquid AI’s LFM Open License; commercial eligibility and terms depend on an organization’s annual revenue.Starting Price: $0.08/MTok -
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GUMU
GUMU
As more and more firms move to IT systems to efficiently manage business processes, the need for integrated management systems is skyrocketing. CRM and ERP software are at the heart of driving these processes smoothly. Greytrix, with its decade-old expertise and globally recognized partnership with Sage, provides the best ERP and CRM solutions. It also is the architect and developer of GUMU™ Cloud, a unique cloud integration system that enables smooth integration of the two systems. It is a framework built on modern technology to integrate two systems in a hassle-free plug-and-play method. GUMU™ allows users to have a powerful integration tool without having an on-premise server-class separate machine for integration. GUMU™ enables easy integration between Sage ERPs (Sage X3, Sage Intacct, Sage 100, Sage 300), Acumatica, QuickBooks with CRM systems (MS Dynamics 365, Sage CRM and Salesforce), eCommerce (Adobe Commerce, formerly known as Magento, Shopify), and POS. -
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RelaySwitch
Uplink Switch
RelaySwitch is a hosted AI model API gateway for developers who want to call models from multiple providers through a shared endpoint and account. It exposes an OpenAI-compatible API and supports the Anthropic Messages format for Claude models, allowing compatible SDKs and developer tools to connect by changing the base URL and API key. Its catalog covers chat, image, video, speech and 3D models, with model identifiers and token rates. Usage is billed from a prepaid USD balance; input and output rates are listed separately, and cached input may cost less where supported. Customers can add funds through supported card and digital-asset payment methods, without a monthly subscription. RelaySwitch is intended for developers and teams building applications and agents with hosted AI models, and provides API documentation, model listings and setup guides for supported SDKs and tools.Starting Price: $10 prepaid
