Requesty Alternatives

FinOpsly is an AI Cost Governance platform. It brings AI, cloud, data platform and SaaS spend into one attribution, policy and control layer, so enterprises can price a workload before building it, attribute every dollar to an owner, hold spend inside budget under policy, and prove what landed in run-rate. Your AI invoice is not what your AI costs. One request draws on model tokens, retrieval, warehouse queries, GPU capacity and storage, and only the first shows up on the AI bill. FinOpsly resolves all of it, plus the seats in procurement and the compute in an untagged cloud account, to the same dimensions: owner, team, application, line of business, customer and tenant. An AI initiative's full cost becomes one figure, charged back through one hierarchy in one cycle. Workforce AI is the tools employees use: seats and per-user token draw across GitHub Copilot, Cursor, ChatGPT Enterprise and Microsoft 365 Copilot. Application AI is the AI your product ships: tokens, compute and data joined into cost-to-serve across OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex AI, SageMaker and Databricks. PLAN. Price a workload from its architecture before any resource exists, across model APIs, GPU capacity, data platform consumption and storage, with assumptions visible. Compare it across candidate models on your measured usage. EXPLAIN. Attribute spend to owner, team, application, line of business and business unit across 9+ hierarchy levels. Unified tagging reconciles providers that tag inconsistently, and AI-driven bulk labeling closes large key estates. Unattributed spend is reported in dollars. ACT. Budgets per project, team and API key, with daily burn-rate monitoring. Anomaly detection with root cause, routed to the owner. Waste detection using FinOpsly's own algorithms and ML models. Commitment planning across AWS, Azure and Google Cloud. Policy-driven parking of idle compute. PROVE. Chargeback across AI, cloud, data and SaaS in one cycle. Realized savings tracked into run-rate against a no-action baseline. Cost per call, cost per active user, and cost-to-serve per customer and tenant. proof: 100% attribution of AI spend; chargeback from 12.4 days to under one day across 9+ levels; 26% realized savings in AWS and 17%+ in Azure at a payments client. Built for CIOs, CTOs and platform leaders accountable for technology spend, FinOps and finance teams running chargeback, and engineering teams who need cost signal before they decide

OpenRouter is an AI model routing platform that gives developers access to hundreds of models through a single unified API. It connects users with models from providers such as OpenAI, Anthropic, Google, Meta, Mistral, DeepSeek, Qwen, xAI, and many others. The platform supports text, image, video, and audio generation while allowing developers to use one API key and a consistent interface across providers. OpenRouter can route requests based on price, performance, and availability, with fallback options that help maintain service when a provider experiences downtime. It also offers configurable data policies so organizations can control which providers receive prompts and how requests are handled. Developers can purchase credits, choose from more than 500 active models across over 80 providers, and integrate OpenRouter using an OpenAI-compatible API.

Septor Labs is a hosted AI gateway and model router for developers building AI agents, copilots, and LLM-powered applications. It provides a unified API for routing requests to supported models by priority, weight, active connections, or latency. Users can select a model or enable automatic model selection, turn on semantic caching, and configure API keys with individual credit budgets and optional IP allow-lists. Septor Labs supports OpenAI-style and Anthropic-style request formats, so compatible clients can connect through a shared gateway. A web console provides model and usage controls, while prepaid credits support pay-as-you-go usage. The service is intended for developers and teams integrating language-model capabilities into agents, copilots, and other software products.

Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!

​LiteLLM is a versatile platform designed to streamline interactions with over 100 Large Language Models (LLMs) through a unified interface. It offers both a Proxy Server (LLM Gateway) and a Python SDK, enabling developers to integrate various LLMs seamlessly into their applications. The Proxy Server facilitates centralized management, allowing for load balancing, cost tracking across projects, and consistent input/output formatting compatible with OpenAI standards. This setup supports multiple providers. It ensures robust observability by generating unique call IDs for each request, aiding in precise tracking and logging across systems. Developers can leverage pre-defined callbacks to log data using various tools. For enterprise users, LiteLLM offers advanced features like Single Sign-On (SSO), user management, and professional support through dedicated channels like Discord and Slack.

TensorZero is an open source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation. It creates a feedback loop for optimizing LLM applications, turning production metrics and human feedback into smarter, faster, and cheaper models and agents. The gateway lets teams integrate once and access every major LLM provider through a single unified API, including API and self-hosted models, with support for tool use, structured outputs, batch inference, embeddings, multimodal inputs, caching, routing, retries, fallbacks, load balancing, granular timeouts, usage tracking, custom rate limits, and provider-key protection. Built for performance in Rust, TensorZero is designed for extreme throughput and low-latency production workloads while still letting teams adopt only the components they need. Its observability layer stores inferences and feedback in the user’s own database, available programmatically or through the open source UI.

ModelLane is an AI inference gateway and routing control plane for developers and organizations using multiple language-model providers. It offers an OpenAI-compatible API for sending requests to hosted, private, or self-hosted models. Teams can define routing policies (“Lanes”) by cost, latency, availability, data retention, and region, with provider failover, retries, credential isolation, and route-level usage and spend visibility. Documented connectors include OpenAI, Anthropic, Google, Mistral, Groq, and DeepSeek, plus local serving tools such as Ollama and vLLM. An MCP interface exposes model-layer operations. Use cases include consolidating provider APIs, choosing routes for different workloads, maintaining continuity when a provider is unavailable, and monitoring inference activity. Deployment options include hosted service, dedicated deployment, and a customer VPC.

Bifrost is a high-performance AI gateway that unifies access to 20+ providers OpenAI, Anthropic, AWS, Bedrock, Google Vertex, Azure, and more, through a unified API. Deploy in seconds with zero configuration and get automatic failover, load balancing, semantic caching, and enterprise-grade governance. In sustained benchmarks at 5,000 requests per second, Bifrost adds only 11 µs of overhead per request.

Waterfall is a credit infrastructure for platforms building on large language models, designed to turn AI usage into a business model without requiring teams to build their own billing stack. It gives each user, agent, or team a stablecoin-backed credit wallet, then meters every model call by provider, model, token count, and cost. Requests can be routed through the Waterfall Gateway or integrated through TypeScript and Python SDKs, with usage attributed to the correct wallet in real time. Each API call settles atomically against the wallet as it happens, so credits decrease, and revenue is recognized per request instead of through delayed invoices and manual reconciliation. Waterfall supports more than 300 models across providers such as OpenAI, Anthropic, DeepSeek, and xAI, allowing products to use multiple AI services while maintaining one accounting layer.

LLMeter is an open source AI cost monitoring platform that gives developers one dashboard for tracking spend across OpenAI, Anthropic, DeepSeek, OpenRouter, Mistral, and Azure OpenAI. Teams connect read-only provider keys and can see real costs, daily trends, model-level breakdowns, and optimization opportunities in about 30 seconds without installing an SDK, changing endpoints, or routing production traffic through a proxy. Because requests continue going directly to the model provider, LLMeter adds no latency, does not become a point of failure, and never sees prompts or completions. Budget alerts warn teams before spending crosses daily or monthly limits, while anomaly detection identifies unexpected usage spikes before they grow. The dashboard shows which providers, models, endpoints, customers, and environments are driving costs, and OpenRouter support extends visibility across more than 500 models.

Concentrate AI is the LLM gateway for fast-growing teams, one API for every major LLM provider, with routing, spend, logs, and controls in one place. It helps teams securely access, use, and manage AI through a single API, so every request can find the smarter, faster, cheaper model for the workflow or task. Teams can access 130+ models, benchmark speed, quality, and cost, and route each workload to the best fit without wiring separate provider APIs into every environment. Support bots, coding agents, internal tools, chat, and batch jobs do not need the same model or the same route, so Concentrate lets teams pick a model slug, limit allowed providers, sort by live latency, use fallbacks, and reroute traffic when a provider slows down, errors, or hits a rate limit. It also gives engineering, finance, security, and leadership a shared view of AI usage with request-level logs, models, provider, duration, token counts, spend, error rates, alerts, and exports.

Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode and Jupyter, automated dependency management, and expert-built app templates. Deployment options are flexible, supporting public clouds, on-premises clusters, and Kubernetes environments. Anyscale Jobs and Services enable reliable production-grade batch processing and scalable web services with features like job queuing, retries, observability, and zero-downtime upgrades. Security and compliance are ensured with private data environments, auditing, access controls, and SOC 2 Type II attestation.

Experiential is an AI model gateway and inference platform for software developers and organizations building AI-enabled products or internal applications. It provides a unified API for routing requests to hosted model providers, customer-supplied provider accounts, and self-hosted or custom models, with OpenAI-compatible and Anthropic API access. Teams can manage API keys, budgets and usage limits, attribute costs to keys or agents, monitor requests, and configure provider routing and fallback behavior. The hosted service includes a free plan and paid monthly plans, while the open-source gateway can also be self-hosted. Enterprise plans add organization controls and data-residency options; paid plans also include model-optimization features, and enterprise customers can commission a model trained on their traffic. Developers can connect compatible applications and coding agents by changing their API endpoint and credentials.

WrangleAI is an enterprise-grade platform that gives organizations visibility, control, and governance over their AI usage and spending. It acts as a “control plane” for generative-AI tools (like GPT-4, Claude, Gemini, and more), providing real-time usage tracking across providers, cost intelligence, infrastructure monitoring, and spend caps so companies can avoid runaway budgets. WrangleAI offers AI observability, helping teams understand which models are being used, by whom, and for what purposes, plus routing intelligence that can redirect workloads to more cost-effective models while maintaining output quality. It also includes governance features such as role-based access control and compliance support (e.g., for SOC 2 / ISO 27001 standards), enabling finance, engineering, and leadership teams to coordinate, enforce policies, and get actionable recommendations for optimizing AI spending and usage.

OrcaRouter is an OpenAI-compatible AI model router that sends each prompt to the right model across OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Kimi, and 200+ frontier and open source models. It is built to preserve frontier answer quality while reducing AI inference spend by grading every prompt and routing hard reasoning to frontier models and routine work to lower-cost open source models. The routing is quality-graded, never a blind, cheap-model swap, and each request shows the difficulty grade, selected model, provider, and cost so routes are visible, auditable, and reproducible. Developers can switch by changing the API base URL, while existing SDKs, model names, and streaming behavior continue to work as before. OrcaRouter supports automatic failover, so if a provider goes down mid-stream, traffic can switch transparently, and the application avoids user-facing errors. It also includes API key management with spend caps, model allowlists, rate limits, budget enforcement, and more.

NanoGPT is private pay-per-use AI for every workflow, giving users access to chat, image, video, audio, speech, and embedding models from one platform. It is built to reduce friction for people who want access to strong models without managing many subscriptions or provider accounts, while keeping conversation history local by default and offering private options for sensitive use. NanoGPT brings together models from major providers such as ChatGPT, Claude, Gemini, DeepSeek, Llama, DALL-E, Stable Diffusion, Flux, Recraft, and more, so users can switch between tools depending on the task. It supports conversations, coding, creative writing, image generation, video generation, audio creation, text-to-speech, web search, file uploads, and model comparison in the same interface. Its model pages let users browse and discover AI language models for conversations, coding, and creative writing, as well as image models for creative projects.

flo2 is an LLM gateway and router that provides access to major AI model providers (OpenAI, Anthropic, Groq, Cerebras, DeepInfra) through one unified, OpenAI-compatible API. Smart routing picks the cheapest or fastest model per request. Automatic fallback keeps applications running when a provider goes down. Racing mode runs requests across providers in parallel. Full cost accounting per request, per model, per project. Developers use their own provider keys via flo2.com — RapidAPI's testing tier includes free tokens for evaluation.

Klique is an enterprise AI control plane that helps organizations manage AI models, applications, agents, and computing resources through a unified platform. The software combines intelligent model routing, AI service governance, and GPU orchestration to optimize performance, infrastructure utilization, and operational costs. Its smart routing engine directs AI requests to appropriate models based on cost, latency, data sensitivity, and organizational policies. Centralized governance capabilities include token budgets, usage quotas, role-based permissions, single sign-on, and audit logging across AI services. Klique also supports GPU resource pooling, fractional GPU sharing, workload scheduling, and automated allocation of computing resources across cloud and on-premises infrastructure. The platform integrates with Kubernetes, cloud providers, AI model APIs, and developer tools while supporting self-hosted, hybrid, and air-gapped deployments.

FastRouter is a unified API gateway that enables AI applications to access many large language, image, and audio models (like GPT-5, Claude 4 Opus, Gemini 2.5 Pro, Grok 4, etc.) through a single OpenAI-compatible endpoint. It features automatic routing, which dynamically picks the optimal model per request based on factors like cost, latency, and output quality. It supports massive scale (no imposed QPS limits) and ensures high availability via instant failover across model providers. FastRouter also includes cost control and governance tools to set budgets, rate limits, and model permissions per API key or project, and it delivers real-time analytics on token usage, request counts, and spending trends. The integration process is minimal; you simply swap your OpenAI base URL to FastRouter’s endpoint and configure preferences in the dashboard; the routing, optimization, and failover functions then run transparently.

AI Cost Board is an AI API observability and cost control platform that brings costs, requests, tokens, latency, errors, and usage from multiple model providers into one real-time dashboard. Applications route LLM traffic through a single proxy endpoint, while requests are forwarded to the connected provider and logged with model, token, status, timing, costs, input, output, and raw JSON context. In most cases, teams only replace the provider base URL and use an AI Cost Board project key, keeping the original request structure intact. It supports providers including OpenAI, Anthropic, and Google Gemini, with a consistent setup that standardizes usage data across integrations. Cost analytics break spending down by project, provider, model, and timeframe, showing trends, cost per request, success rates, and operational performance. Searchable request logs help developers inspect payloads, troubleshoot failures, compare models, and investigate slow or expensive calls.

Tokonomics is an AI cost metering proxy that sits between your app and any LLM provider. One URL change gives you real-time cost tracking, budget alerts, and hard spending caps across OpenAI, Anthropic, DeepSeek, Google Gemini, Mistral, Groq, and more. How it works: Replace your LLM base URL with Tokonomics, keep your existing code. Every API call is logged with token counts, cost (8-decimal USD precision), latency, and custom tags for per-team or per-feature attribution. Key features: - Budget alerts via email, Slack, or Teams at configurable thresholds - Hard spending caps that block requests when monthly budget is exceeded - Analytics dashboard with spend-by-model, daily trends, and cost optimization reports - BYOK (Bring Your Own Keys) with AES-256 encryption - Rate limiting per API key - Works with any language or HTTP client (PHP, Python, Node.js, Go, Ruby)

PromptUnit cuts your AI API bill without hurting answer quality. Inferio, the engine inside PromptUnit, checks every request your app or agent sends. When a cheaper model is just as good for that request, it uses it; otherwise the request goes to the model you asked for. If you connect keys for more than one provider, the cheaper model can be at another of them. Setup is two settings: point your AI API address at PromptUnit and add your PromptUnit key. Your own provider keys stay yours. Works with OpenAI, Anthropic, Google Gemini, Groq and DeepSeek keys, and with your own OpenRouter key, plus tools like n8n, Open WebUI, LibreChat and Dify. The dashboard shows every request: the model asked for, the model that answered, what it cost and what it saved. It also groups requests into the steps of your app and shows what each step costs. Pricing: the first $5 of savings is free, then 20% of what PromptUnit saves you, billed weekly. Nothing if it saves nothing.

Vercel AI Gateway is a unified AI infrastructure platform that allows developers to access, manage, and route requests across hundreds of AI models and providers through a single API interface. Built as part of the Vercel AI ecosystem, the platform supports text, image, and video generation models from providers such as OpenAI, Anthropic, SpaceXSI, and others while simplifying authentication, billing, observability, and failover management. Developers can use one API key and centralized dashboard to integrate multiple AI providers into applications without managing separate provider accounts or infrastructure. The platform also includes built-in routing, automatic failovers, usage tracking, unified billing, and compatibility with SDKs such as the Vercel AI SDK, enabling faster development and more resilient AI-powered applications.

BaronRouter is an AI gateway and chat platform that brings many leading AI models and providers into one unified interface. Users can chat with different models, compare responses side by side, save prompts, create projects, use public personas, upload files, and keep conversation history in one place. BaronRouter is built around reliability and model choice. Its smart router can select a suitable model for a task, while automatic retry and fallback help keep conversations working when a provider is rate-limited, unavailable, or fails. The platform also includes persistent memory, shared workspaces, prompt and persona galleries, model performance stats, admin controls, usage analytics, and an OpenAI-compatible public API for developers. Developers can call BaronRouter through standard OpenAI SDK clients, including support for public persona endpoints such as persona-based chat completions.

Spendline is a hosted AI gateway and cost-management tool for software companies that offer AI features in their products. It routes model requests through a gateway and records usage and cost by customer and agent, helping engineering and finance teams compare AI spend with customer revenue. Teams can set nested budgets for companies, teams, agents, and customers; configure alerts and approval workflows; and apply rules to route requests to lower-cost models. Spendline also provides usage reporting and month-end checks that compare recorded usage with provider invoices. The service supports multiple model providers and offers controls for managing AI usage across customer-facing applications.

Router is an LLM gateway built to reduce inference costs by matching each request to the lowest-cost model that still meets performance needs. It provides one endpoint and one API key for accessing multiple closed and open-source AI models from providers such as OpenAI, Anthropic, Grok, Fireworks, and others, helping developers avoid wiring applications to providers one at a time. Requests go through Router first, where usage, model, provider, and cost can be tracked before eligible workloads are routed to a more efficient option when quality will not be affected. Router Strategies let developers define cost and performance priorities for different types of requests or use benchmarked defaults based on real production workloads. It responds to live latency, availability, failures, and rate limits, and eligible requests can be moved to another available model when a provider cannot serve them.

Cloptima is an AI and cloud FinOps platform that brings LLM spend governance, multicloud cost intelligence, Kubernetes optimization, query analysis, and engineering cost controls into one operating model. Its AI gateway lets teams use their own OpenAI, Anthropic, Gemini, Vertex AI, and Amazon Bedrock credentials behind encrypted controls, then apply virtual keys, model policies, token limits, budgets, guardrails, and attribution before calls reach providers. Spend analytics break down usage by provider, model, team, application, environment, user, agent session, tool, workflow, and dimensions, while agent controls track retries, loops, tool calls, and runaway-cost risk. Exact and semantic response caching can reduce repeated usage, and intelligent routing can shift eligible traffic to cheaper or faster models with canary rollout and rollback if quality, latency, or errors regress.

ZenLLM is an AI cost optimization platform for engineering teams running LLM applications in production. It connects provider invoices to the application behavior behind them, showing which prompts, workflows, models, customers, retries, and request paths are driving spend. Teams send request-level telemetry through the ZenLLM SDK and can attach business context such as workflow, owner, customer, team, or product feature without storing prompt or response content. It monitors token usage, model selection, latency, errors, retries, and cost, then surfaces the waste patterns hidden by aggregate provider dashboards. It detects context accumulation when conversations or agents resend growing histories, premium-model overuse on low-risk work, retry loops that repeat expensive context, stale system prompts, routing mistakes, anomalies, and weak cost ownership.

Track costs, usage, and latency for GPT applications with one line of code. Trusted by leading companies building with OpenAI. We will support Anthropic, Cohere, Google AI, and more coming soon. Stay on top of your costs, usage, and latency. Integrate models like GPT-4 with Helicone to track API requests and visualize results. Get an overview of your application with an in-built dashboard, tailor made for generative AI applications. View all of your requests in one place. Filter by time, users, and custom properties. Track spending on each model, user, or conversation. Use this data to optimize your API usage and reduce costs. Cache requests to save on latency and money, proactively track errors in your application, handle rate limits and reliability concerns with Helicone.

Kilo Gateway is a universal AI inference gateway that routes LLM requests to any provider through one standardized endpoint, giving developers access to hundreds of hosted and open models without rewriting their applications for each provider. It provides unified access to models from Anthropic, OpenAI, Mistral, and other providers, while also supporting bring-your-own-key configurations that let teams connect existing provider credentials through centralized infrastructure. The gateway is compatible with standard AI SDKs, making it possible to switch providers while keeping the same integration surface. Its infrastructure handles routing complexity and load balancing across direct providers and external gateways to improve availability and resilience. Auto Model can route each request to the best available model while keeping routing decisions, model behavior, and usage visible and controllable.

discode is an AI chat platform built around one input field, 100+ AI models, and automatic model selection, so users choose the rhythm, not the algorithm. Instead of juggling multiple subscriptions, tabs, benchmarks, and provider limits, users ask a question and discode picks the right model for the job. Every request is analyzed by topic, complexity, and language, then routed to the best available model based on quality, speed, sustainability, and the user’s own settings. Light tasks can go to fast, resource-efficient models, while harder tasks can be sent to specialist or frontier models when needed. discode also explains which model was chosen and why, keeping routing transparent instead of turning it into a black box. Its Turntables let users weigh what matters most, such as smarter output, faster answers, or better eco impact, while Smart Prompting quietly optimizes prompts in the background for different model families and domains.

TokenAtlas is an AI FinOps and cost intelligence platform that helps teams understand, forecast, and optimize AI costs before they become expensive. Users describe a workload by entering the model, input and output token volumes, request counts, and growth assumptions, and TokenAtlas prices the scenario against a maintained catalog of published API rates. The cost modelling dashboard brings configured workloads into one view, while model comparison places provider and model options side by side using transparent assumptions. What-if scenario planning shows the cost impact of launching a new prompt, agent, model swap, retrieval pipeline, or traffic increase before it reaches production. Cost risk analysis identifies the workloads most sensitive to changes in volume, prompt size, or model choice, and benchmark comparisons show how a modeled model mix compares with typical AI product and infrastructure profiles.

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.

AnonRouter is a hosted AI model router and API for developers building AI applications. It provides one OpenAI-compatible endpoint for accessing models from multiple providers, with a model catalog, per-model pricing and privacy labels, routing, and automatic failover. Developers can connect compatible clients by configuring the endpoint and an API key, or use the browser-based Chat and Studio for text, image, and speech models. Requests are billed from prepaid credits, with usage priced by model and additional fees on credit purchases. Depending on the selected model and provider, requests may use standard processing, private handling, a trusted execution environment, or end-to-end encryption where available. AnonRouter is designed for developers, AI teams, and individual users who want to build, connect, or test applications with multiple AI models through a shared interface.

Mavvrik is an AI and hybrid infrastructure cost management platform that gives finance, FinOps, IT, and engineering teams one control center for GenAI, autonomous agents, GPUs, cloud, on-premises systems, Kubernetes, data platforms, and SaaS. It unifies cost, usage, and telemetry signals from AWS, Azure, Google Cloud, Oracle, VMware, NVIDIA, OpenAI, Anthropic, Gemini, Snowflake, Databricks, and LiteLLM, creating a single source of truth across the technology stack. Teams can track every model call, agent interaction, GPU hour, workload, service, and resource, then allocate spending by customer, product, feature, project, application, environment, team, or cost center. Cost-to-serve and unit-economics analysis reveal margin drains, expensive workloads, and the true cost of delivering each offering. Real-time anomaly detection and alerts identify usage before it becomes a budget surprise, while predictive forecasting helps organizations model cloud, GPU, and AI expenses.

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.

Factory Router is an automatic model-selection system for autonomous software engineering workflows, designed to deliver frontier performance at lower cost and with higher reliability. Instead of expecting engineers to manually choose the best model for every task, Factory Router automatically selects the right model for each Droid session, drawing from a diverse pool of frontier and efficient models. Simple questions, mechanical refactors, documentation updates, small bug fixes, search-heavy investigations, and other routine work can be handled by efficient models, while harder work that genuinely needs deeper reasoning can stay on frontier models. If the selected model struggles to complete a task, Factory Router can move the session to a more capable model to reliably preserve high-quality outcomes. It also routes across models, providers, and capacity sources when endpoints degrade, rate limits hit, or capacity becomes constrained, helping Droid sessions keep working.

Modelflare is a hosted AI API gateway for developers building applications, agents, and workflows that use models from multiple providers, including GPT, Claude, Gemini, Grok, and DeepSeek. It provides a shared API key and console for OpenAI-compatible chat and Responses, Anthropic Messages, and provider-specific image and video interfaces. Developers can compare models and routing groups, configure primary routes and ordered fallback groups, or use Smart API Keys to select among available routes according to a routing strategy. API keys can be separated by project and managed with controls such as quotas, expiration dates, and model or IP restrictions. The service records request-level usage, token counts, routing details, and costs, with pricing based on the selected model, group, and applicable billing unit. Documentation includes setup guides for SDKs, coding agents, plugins, and workflow tools.

LowRouter is a European AI gateway for agents and apps, providing one API key and one bill in euros for language models from European and international providers. Set routing rules per API key, including EU-sovereign providers only, lower-carbon routing, lower-cost routing, or a combination. Responses report the provider and region, with an estimated carbon figure when model data supports it. Coding agents such as OpenCode, Claude Code, and Cline can use LowRouter as a custom provider. Apps built with LangChain or the OpenAI SDK can also connect. Aliases let you switch models or providers without changing code, and automatic routing can send eligible requests to another provider when a route fails. The public model catalogue can be searched by sovereignty and carbon intensity. Tokens are billed at provider prices without a per-token markup; credit top-ups carry a fee, and there is no subscription. LowRouter is operated by Carbonifer SAS in Nantes, France.

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.

SatGate is an agent authority and accountability Layer that governs what AI agents can access, spend, delegate, and execute before a request reaches an API, model, MCP tool, or paid external service. Deployed as an HTTP reverse proxy and MCP proxy, it applies scoped authority, per-agent budgets, route policies, and next-request revocation directly in the request path. Agents badge in once through existing Kubernetes, AWS, or OIDC identity, and SatGate Mint exchanges that identity for a cryptographically signed Macaroon containing limits for scope, budget, expiration, and delegation depth. Capabilities can only become more restrictive as they move through agent chains, preventing sub-agents from escalating beyond the authority they receive. Observe mode measures requests and attributes usage by agent, team, tool, route, and cost center without changing workflows; Control mode enforces hard budget caps before expensive or unauthorized work executes.

Sudo offers “one API for all models”, a unified interface so developers can integrate multiple large language models and generative AI tools (for text, image, audio) through a single endpoint. It handles routing between different models to optimize for things like latency, throughput, cost, or whatever criteria you choose. The platform supports flexible billing and monetization options; subscription tiers, usage-based metered billing, or hybrids. It also supports in-context AI-native ads (you can insert context-aware ads into AI outputs, controlling relevance and frequency). Onboarding is quick: you create an API key, install their SDK (Python or TypeScript), and start making calls to the AI endpoints. They emphasize low latency (“optimized for real-time AI”), better throughput compared with some alternatives, and avoiding vendor lock-in.

RouteAI is an AI API routing platform that helps developers and enterprises reduce inference costs while maintaining speed, reliability, and model flexibility. The platform provides one OpenAI-compatible API for accessing multiple mainstream AI models through global routing infrastructure. Developers can migrate existing OpenAI-based integrations by changing the base URL and using their RouteAI API key. RouteAI supports intelligent routing, load balancing, global edge nodes, real-time monitoring, API key permissions, alerts, and enterprise-grade security. The platform also provides SDK support, documentation, online debugging tools, and examples for languages such as Python, Node.js, Java, Go, and C#. Built for teams running production AI workloads, RouteAI helps simplify model access, lower infrastructure complexity, and deliver faster AI responses through one unified API.

Substrate is the platform for agentic AI. Elegant abstractions and high-performance components, optimized models, vector database, code interpreter, and model router. Substrate is the only compute engine designed to run multi-step AI workloads. Describe your task by connecting components and let Substrate run it as fast as possible. We analyze your workload as a directed acyclic graph and optimize the graph, for example, merging nodes that can be run in a batch. The Substrate inference engine automatically schedules your workflow graph with optimized parallelism, reducing the complexity of chaining multiple inference APIs. No more async programming, just connect nodes and let Substrate parallelize your workload. Our infrastructure guarantees your entire workload runs in the same cluster, often on the same machine. You won’t spend fractions of a second per task on unnecessary data roundtrips and cross-region HTTP transport.

SeedRouter is a usage-based API platform for accessing image, video, language, and audio AI models through one API key and prepaid balance. It provides OpenAI-compatible endpoints for language models and asynchronous task APIs for media generation. Developers can manage keys, monitor request status, and review model-level usage and costs in a dashboard. SeedRouter is designed for developers and product teams integrating multiple AI model families into applications.

TensorBlock is an open source AI infrastructure platform designed to democratize access to large language models through two complementary components. It has a self-hosted, privacy-first API gateway that unifies connections to any LLM provider under a single, OpenAI-compatible endpoint, with encrypted key management, dynamic model routing, usage analytics, and cost-optimized orchestration. TensorBlock Studio delivers a lightweight, developer-friendly multi-LLM interaction workspace featuring a plugin-based UI, extensible prompt workflows, real-time conversation history, and integrated natural-language APIs for seamless prompt engineering and model comparison. Built on a modular, scalable architecture and guided by principles of openness, composability, and fairness, TensorBlock enables organizations to experiment, deploy, and manage AI agents with full control and minimal infrastructure overhead.

Braintrust is an AI observability and evaluation platform designed to help teams build, monitor, and improve AI systems in production. It enables users to capture and inspect real-time traces of AI interactions, including prompts, responses, and tool usage. The platform allows teams to measure performance using automated and human evaluations to ensure output quality. Braintrust helps identify issues such as hallucinations, regressions, and performance drops before they impact users. It supports prompt and model comparisons, making it easier to optimize AI workflows over time. With scalable trace ingestion and real-time monitoring, teams gain full visibility into how their AI systems behave. The platform integrates with multiple programming languages and tools, allowing developers to work within their existing tech stack. Overall, Braintrust provides a comprehensive solution for maintaining and improving AI quality at scale.

FinOps LLM is an AI cost management and LLM observability platform for engineering teams running production GenAI. It makes token spend visible across OpenAI, Anthropic, Amazon Bedrock, Google Gemini, Azure, Groq, and other providers and reconciles internal usage data against provider invoices. Token-level costs can be filtered by provider, model, feature, team, customer, environment, and custom dimensions, giving every dollar a clear owner. Attribution and chargeback tools map usage to product surfaces and customer cohorts, support showback, and export data to NetSuite, QuickBooks, CSV, or APIs. Real-time anomaly detection monitors spend, latency, and quality against rolling feature baselines, sending alerts through Slack, PagerDuty, email, or webhooks when behavior changes. Optional budget enforcement and auto-throttling can stop runaway agents, retries, or model shifts before they become expensive.

LLM Gateway is a fully open source, unified API gateway that lets you route, manage, and analyze requests to any large language model provider, OpenAI, Anthropic, Gemini Enterprise Agent Platform, and more, using a single, OpenAI-compatible endpoint. It offers multi-provider support with seamless migration and integration, dynamic model orchestration that routes each request to the optimal engine, and comprehensive usage analytics to track requests, token consumption, response times, and costs in real time. Built-in performance monitoring lets you compare models’ accuracy and cost-effectiveness, while secure key management centralizes API credentials under role-based controls. You can deploy LLM Gateway on your own infrastructure under the MIT license or use the hosted service as a progressive web app, and simple integration means you only need to change your API base URL, your existing code in any language or framework (cURL, Python, TypeScript, Go, etc.)

Keep track of your OpenAI usage and costs with AI Spend and never be surprised again. AI Spend offers user-friendly cost tracking with a dashboard and notifications that passively monitor your usage and costs. The analytics and charts provide insights that help you optimize your OpenAI usage and avoid billing surprises. Get daily, weekly, and monthly notifications with your spending. Discover which models and how many tokens you're using. Get clear insights into how much OpenAI is costing you.