{"schemaVersion":1,"profileUrl":"https://nowen.ai/agents/litellm-ai","markdownUrl":"https://nowen.ai/agents/litellm-ai.md","jsonUrl":"https://nowen.ai/agents/litellm-ai.json","name":"LiteLLM","legalName":"Berrie AI Incorporated","website":"https://litellm.ai","location":"San Francisco, California, USA","address":{"city":"San Francisco","state":"California","country":"USA"},"industry":"AI Infrastructure and Enterprise Governance Software","deliveryModel":"software","status":{"trust":"unclaimed","text":"Unclaimed: compiled by Nowen from public sources, not reviewed by the company"},"updatedAt":"2026-10-30T03:51:44.036Z","summary":"An independent software company building open-source infrastructure to help teams operate AI systems with consistent access, governance, and cost control.","description":"LiteLLM is an independent software company that builds open-source developer infrastructure for operating AI in production. It helps platform teams and developers connect applications to language models, agents, and tools through a consistent interface, while managing access, usage, costs, routing, and security. Its offerings support self-hosted, cloud, on-premises, and air-gapped deployments, serving organizations that need to provide reliable, governed AI capabilities to their teams.","mission":"Help teams operate AI in production by making access to models, agents, and tools consistent, secure, and manageable.","directory":{"industryName":"AI Infrastructure and Enterprise Governance Software","agentCount":4,"indexable":false,"hubUrl":"https://nowen.ai/industry/ai-infrastructure-and-enterprise-governance-software"},"aiReaderFamilies":["Perplexity"],"products":[{"name":"LiteLLM AI Gateway","type":"Platform","url":"https://www.litellm.ai/ai-gateway","summary":"Unify access to models, tools, and agents while helping teams govern usage, manage spend, and deploy AI services in their own infrastructure.","description":"LiteLLM AI Gateway is an open-source, self-hosted gateway that connects applications to 140+ LLM providers, 1,800+ models, MCP servers, and agents through a unified API. It provides virtual keys, access controls, budgets, rate limits, usage and spend tracking, guardrails, request logging, and model routing. MCP servers and agents can be registered behind shared gateway endpoints, with access controls and logging applied alongside model calls. The gateway supports deployment in a customer's cloud, on-premises, on Kubernetes, or in air-gapped environments. Enterprise extends the gateway with features including SSO, SCIM, audit logs, secret-manager integrations, a multi-region control plane, onboarding, upgrade assistance, and support with response-time SLAs.","pricing":{},"features":[{"name":"Unified API access","value":"Connect Models, Tools, And Agents Through One API","valueDescription":"Give applications a consistent gateway interface for models, MCP tools, and agents, and change model configurations without changing application code."},{"name":"Virtual key management and access controls","value":"Control Access Across Keys, Teams, And Organizations","valueDescription":"Provide scoped access for applications, users, teams, and organizations. Agent and MCP calls can use the same keys and access controls as model calls."},{"name":"Budgets and rate limits","value":"Set Spend And Request Limits","valueDescription":"Apply usage limits at the levels identified by the organization and stop requests when budget caps are reached."},{"name":"Model routing and fallbacks","value":"Route Requests Across Models And Providers","valueDescription":"Direct traffic to configured models and providers, and use fallbacks to handle provider outages."},{"name":"Request logging and audit trails","value":"Record Requests And Administrative Activity","valueDescription":"Review request activity and administrative changes, including agent and tool calls, and send logs to supported observability systems."},{"name":"Self-hosted and air-gapped deployment","value":"Run The Gateway In Your Infrastructure","valueDescription":"Deploy the gateway in cloud, on-premises, Kubernetes, or air-gapped environments, keeping AI traffic and provider keys within your infrastructure."},{"name":"Enterprise support","value":"Get Support With Response-Time SLAs","valueDescription":"Access support with response targets for production incidents and security patches. Custom SLAs are also available."},{"name":"Enterprise authentication","value":"Manage Access With Enterprise Identity","valueDescription":"Connect enterprise identity and provisioning workflows through SSO and SCIM, and use OIDC or JWT authentication for gateway access."},{"name":"Usage and spend tracking","value":"Track Usage And Attribute Spend","valueDescription":"See which users, teams, tools, agents, and services drive activity and costs, with attribution to support chargeback and organizational oversight."},{"name":"Load balancing","value":"Balance Requests Across Deployments","valueDescription":"Distribute requests across configured models, providers, regions, and keys."},{"name":"Cost-based and automatic routing","value":"Route Requests To Suitable Models","valueDescription":"Choose a lower-cost deployment when it can serve the request, or route prompts to models according to their complexity."},{"name":"Guardrail enforcement","value":"Apply Guardrails To AI Requests","valueDescription":"Configure checks and policies for requests, including controls for sensitive information, prompt injection, and secrets."},{"name":"MCP server gateway","value":"Manage And Connect MCP Servers","valueDescription":"Make registered MCP servers available through shared endpoints, control which keys, teams, or organizations can access them, and connect servers using supported transports. OpenAPI specifications can be converted into MCP servers, and tools can also be called through a REST endpoint without an LLM."},{"name":"Agent gateway","value":"Connect And Govern Agent Calls","valueDescription":"Route supported agent calls through the gateway and manage their access, logging, usage, and spend alongside model calls."},{"name":"Secret management and key rotation","value":"Manage Secrets And Rotate Keys","valueDescription":"Use secret-manager integrations and key rotation to manage gateway credentials."},{"name":"Enterprise onboarding and upgrade assistance","value":"Get Onboarding And Live Upgrade Help","valueDescription":"Receive dedicated onboarding and help from the LiteLLM team during live upgrades."},{"name":"Response and semantic caching","value":"Reuse Cached Responses","valueDescription":"Use response and semantic caching to avoid paying repeatedly for the same answer."},{"name":"Admin UI","value":"Manage Gateway Settings In One Dashboard","valueDescription":"Give teams a dashboard for managing keys, models, budgets, MCP servers, and cost data."},{"name":"Multi-region control plane","value":"Operate Across Multiple Regions","valueDescription":"Use a multi-region control plane to support enterprise gateway operations across regions."},{"name":"Low-latency Rust gateway","value":"Reduce Gateway Overhead","valueDescription":"The published benchmark reports 0.66 ms of p99 added latency for the Rust gateway under the stated test conditions."},{"name":"Prompt compression","value":"Send Fewer Prompt Tokens","valueDescription":"Reduce the number of tokens sent in prompts."}]},{"name":"LiteLLM Python SDK","type":"Product","url":"https://www.litellm.ai/about","summary":"Simplify multi-provider LLM development with a consistent Python interface, flexible provider switching, and built-in retries, fallbacks, and cost tracking.","description":"The open-source LiteLLM Python SDK calls more than 100 LLM APIs through a common OpenAI-compatible format. Developers can switch providers by changing the model string without changing response parsing. The SDK supports retries, fallbacks, and cost tracking, and can be used directly from a Python app without running a server.","pricing":{},"features":[{"name":"Multi-provider API calls","value":"Call 100+ LLM APIs","valueDescription":"Use one Python SDK to call more than 100 LLM APIs from Python applications."},{"name":"OpenAI-compatible response format","value":"Keep Response Parsing Consistent","valueDescription":"Handle provider responses in a common format so switching providers does not require changing response-parsing code."},{"name":"Provider switching","value":"Switch Providers By Changing The Model String","valueDescription":"Change the model string to use a different provider while keeping the application's response handling consistent."},{"name":"Provider fallbacks","value":"Fall Back Between Providers","valueDescription":"Use provider fallbacks to keep model calls from depending on a single provider."},{"name":"Direct Python use","value":"Call Providers Without Running A Server","valueDescription":"Use the SDK directly in a Python application, without deploying a separate gateway server."},{"name":"Retries","value":"Retry Model Calls","valueDescription":"Use SDK-supported retries when making model calls."},{"name":"Cost tracking","value":"Track Model Call Costs","valueDescription":"Track costs associated with model calls made through the SDK."},{"name":"Router load balancing","value":"Balance Requests Across Models","valueDescription":"Use the Router to load balance requests across models or providers from a Python application."}]},{"name":"LiteAgents SDK","type":"Product","url":"https://www.litellm.ai/liteagents","summary":"Switch agent harnesses while retaining models, tools, and MCP servers, with native controls and optional Temporal durability.","description":"LiteAgents is an agent SDK with a query() interface modeled after the Claude Agent SDK. Developers can choose among Deep Agents, Claude Agent SDK, Codex, Pydantic AI, and OpenCode harnesses while keeping their model, tools, and MCP servers when changing harnesses. It offers native controls and optional Temporal durability, and supports configuration profiles in Python, JSON, or YAML. The SDK is in alpha and requires Python 3.11 or later.","pricing":{},"features":[{"name":"Agent harness switching","value":"Switch Harnesses Without Rewriting Agents","valueDescription":"Select a different supported harness while using the same query() interface, avoiding the need to rewrite the agent when changing harnesses."},{"name":"Model continuity","value":"Keep Your Model Across Harness Changes","valueDescription":"Change the selected harness without replacing the model configured for the agent."},{"name":"Tool and MCP continuity","value":"Keep Tools And MCP Across Harness Changes","valueDescription":"Retain the agent's tools and MCP servers when switching between supported harnesses."},{"name":"Native harness controls","value":"Configure Harnesses With Native Controls","valueDescription":"Apply native configuration options for the selected harness through LiteAgents profiles."},{"name":"Temporal durability","value":"Add Optional Temporal Durability","valueDescription":"Enable optional Temporal durability for agent workflows."},{"name":"Multi-format profiles","value":"Configure Profiles In Three Formats","valueDescription":"Choose Python, JSON, or YAML to configure LiteAgents profiles."},{"name":"Selective harness installation","value":"Install Only The Harnesses You Use","valueDescription":"Limit installation to the harness integrations needed for your project; the SDK supports Python 3.11 and later."}]},{"name":"LiteLLM Lens","type":"Product","url":"https://www.litellm.ai/about","summary":"Review agent swarm activity and find opportunities to improve it through recorded traces and improvement insights.","description":"LiteLLM Lens is an early-access product that records traces of agent swarms and shows users where they can be improved. It became available on October 1, 2026.","pricing":{},"features":[{"name":"Agent swarm tracing","value":"Record Agent Swarm Activity","valueDescription":"Capture traces of agent swarms so users can review their activity."},{"name":"Agent swarm improvement insights","value":"Identify Swarm Improvements","valueDescription":"Surface areas where agent swarms can be improved, helping users understand where to focus."}]}],"audiences":[],"segments":[{"name":"LLM gateways","description":"Infrastructure for routing application requests across LLM providers through a unified interface, supporting provider portability and structured generation.","size":0.3,"cagr":30,"color":1,"productNames":["LiteLLM AI Gateway","LiteLLM Python SDK"],"methodology":"The search results describe LLM gateway products and capabilities but provide no explicit market-size or growth figures. Using an internal estimate for this nascent infrastructure category, the market is approximately $0.3 billion, with an estimated 30% CAGR as adoption of multi-provider LLM applications and gateway controls expands. These estimates are not directly supported by the supplied sources.","citations":[]},{"name":"AI governance","description":"Centralized control of enterprise access to models, agents, and tools through authentication, permissions, guardrails, credential management, and audit trails.","size":0.89,"cagr":45.3,"color":2,"productNames":["LiteLLM AI Gateway"],"methodology":"The search result’s global report scope states a 2024 AI governance market size of approximately USD 0.89 billion and a 2024–2029 CAGR of 45.3%. This broad market estimate is used as a proxy for the specified AI governance segment; the source does not separately size centralized access control for models, agents, and tools.","citations":[{"url":"https://www.marketsandmarkets.com/Market-Reports/geography/ai-governance-market/uk","text":"Market Size Base Year (Billions) ~USD 0.89 (2024); Growth Rate CAGR of 45.3% from 2024 to 2029"}]},{"name":"AI cost management","description":"Capabilities that help engineering and platform teams attribute AI spending, enforce team and project budgets, and route requests using cost-aware policies.","size":0.8,"cagr":30,"color":3,"productNames":["LiteLLM AI Gateway"],"methodology":"No search results were provided, so no source-based market figures are available. This is a directional estimate for the narrow software segment covering AI spend attribution, budget controls, and cost-aware request routing; it reflects the segment’s early stage and expected expansion alongside enterprise AI adoption.","citations":[]},{"name":"AI observability","description":"Visibility into model, tool, and agent activity through request logging, usage monitoring, and agent swarm tracing to support troubleshooting and improvement.","size":0.6,"cagr":30,"color":4,"productNames":["LiteLLM AI Gateway","LiteLLM Lens"],"methodology":"The search results provide no direct market-size or CAGR estimate for AI observability. The $0.6 billion estimate is an approximate 2025 estimate for this narrower segment, inferred from the broader observability platform market, which is projected to reach $14.2 billion by 2028. The 30% CAGR is an estimate reflecting expected rapid adoption, not a reported AI observability forecast.","citations":[{"url":"https://www.networkworld.com/article/4032218/in-crowded-observability-market-gartner-calls-out-ai-capabilities-cost-optimization-devops-integration.html","text":"Gartner projects the market will grow to $14.2 billion by 2028"}]},{"name":"Agent development frameworks","description":"Frameworks and SDKs for building customizable, model-agnostic agent-powered applications and coding agents with multi-model support and developer extensibility.","size":1.5,"cagr":35.36,"color":5,"productNames":["LiteAgents SDK"],"methodology":"No source provides a standalone estimate for agent development frameworks and SDKs. Estimated 2025 size at roughly USD 1.5 billion, treating frameworks and SDKs as a subset of the broader USD 14.58 billion agentic AI development platform market. The platform market’s 35.36% CAGR is used as a growth proxy; both figures are therefore approximate and the CAGR reflects the broader category, not frameworks alone.","citations":[{"url":"https://www.sphericalinsights.com/blogs/top-25-companies-in-global-agentic-artificial-intelligence-development-platform-market-2026-2035-expert-view-by-spherical-insights","text":"Market Size ... USD 14.58 Billion in 2025 ... at a CAGR of 35.36% during the forecast period 2026–2035."},{"url":"https://www.technavio.com/report/ai-agent-platform-market-industry-analysis","text":"The ai agent platform market size is valued to increase by USD 31.46 billion, at a CAGR of 41.5% from 2025 to 2030."}]}],"faq":[],"comparisons":[],"sources":[{"url":"https://litellm.ai","text":"LiteLLM"},{"url":"https://www.litellm.ai/ai-gateway","text":"LiteLLM AI Gateway"},{"url":"https://www.litellm.ai/about","text":"LiteLLM Python SDK"},{"url":"https://www.litellm.ai/liteagents","text":"LiteAgents SDK"},{"url":"https://www.marketsandmarkets.com/Market-Reports/geography/ai-governance-market/uk","text":"Market Size Base Year (Billions) ~USD 0.89 (2024); Growth Rate CAGR of 45.3% from 2024 to 2029"},{"url":"https://www.networkworld.com/article/4032218/in-crowded-observability-market-gartner-calls-out-ai-capabilities-cost-optimization-devops-integration.html","text":"Gartner projects the market will grow to $14.2 billion by 2028"},{"url":"https://www.sphericalinsights.com/blogs/top-25-companies-in-global-agentic-artificial-intelligence-development-platform-market-2026-2035-expert-view-by-spherical-insights","text":"Market Size ... 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