Contextual AI
- Company typePrivate
- Founded2023
- HeadquartersMountain View, United States
- Headcount11–50
- GTM typeB2B
- OfferingSoftware
Contextual AI firmographics
Firmographics- Name
- Contextual AI
- Legal name
- Contextual AI, Inc.
- Website
- https://contextual.ai
- Company type
- Private
- Founded year
- 2023
- Operating status
- Operating
- Headcount range
- 11–50 employees
- Ownership category
- akta.pro rank
Contextual AI industry classification
Industry- Product category
- Enterprise AI Platform / Context Engineering Software
- NAICS
- Software Publishers (5132)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG) (HDAEANAD)
- akta.pro secondary industries
- Retrieval-Augmented Generation (RAG), Vector Databases & Knowledge Grounding (HDAAACAE), Agents & Autonomous Workflows (Tool Use, Planning, Multi-Agent) (HDAAACAF), Search, Retrieval & Semantic Ranking (BM25/vector, hybrid) (HDAAADAB)
Keywords
Where Contextual AI is headquartered
LocationHeadquarters
- HQ city
- Mountain View
- HQ country
- United States
- HQ region
- North America
Offices2 records
Markets served
Contextual AI business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales
Revenue model
- Platform subscription (SaaS): Subscription-based recurring revenue for access to the Contextual AI Platform, Agent Composer, RAG Component APIs, and pre-built templates. Sold via Order Forms referenced in the Terms of Use. Multi-tenant SaaS, single-tenant SaaS, and private VPC deployment tiers.
- Usage-based component APIs (LMUnit, Parse, Rerank, Generate): Per-token / per-call consumption pricing for the RAG component APIs and LMUnit evaluation model. Per Terms of Use: 'Fees may be subscription-based, flat fees and/or usage-based.' LMUnit offers credits for first 1M tokens with paid tier for additional credits.
- Marketplace / cloud marketplace sales: Revenue transacted via Google Cloud Vertex AI Model Garden where Contextual AI's proprietary model is listed for self-deployment into customer VPCs, alongside AI21 Labs, Mistral AI and other partners.
- Technology licensing: Licensing of proprietary technology to acquirers / partners — evidenced by the Google DeepMind $80M–$90M licensing deal that transferred 20+ researchers along with the technology. Demonstrates the technology is licensable IP for large-scale licensing transactions.
- Professional services & enterprise onboarding: Enterprise sales motions include dedicated support, custom integration, and onboarding services reflected by enterprise pricing tiers, 'contact your Contextual AI representative' language for Agent Composer access, and dedicated customer engineering engagement.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Hybrid | Annual | Quote-based enterprise pricing — not publicly disclosed |
| Usage-based | Pay-as-you-go | LMUnit pay-as-you-go with free tier (first 1M tokens free) |
| Freemium | Monthly | Self-serve / Basic & Agentic Search templates free with sign-up |
Go-to-market motion5 records
Distribution channels5 records
Marketing channels13 records
Contextual AI product offering
Product offeringCore offering
Contextual AI builds an enterprise retrieval-augmented generation (RAG 2.0) platform organized around a Unified Context Layer that combines retrieval, grounding, and agent orchestration to power production-grade AI agents. Its core products include the Contextual AI Platform, Agent Composer (a workflow framework for assembling customized query pipelines with search tools, MCP integrations, and LLMs), LMUnit (a specialized evaluation model for natural language unit tests), and the RAG Component APIs (Parse, Rerank, Generate, LMUnit). The company targets technically demanding industries (semiconductors, aerospace, manufacturing, financial services, legal) and ships pre-built templates such as Basic Search, Agentic Search, Device Log Analysis, and Deep Research.
Product overview
Contextual AI offers a unified context engineering platform for production-grade enterprise AI, centered on an integrated platform-plus-modules architecture. The core Contextual AI Platform provides the unified context layer that powers expert AI agents across advanced industries (semiconductors, aerospace, manufacturing, financial services, legal). On top of this foundation sit Agent Composer (a framework for building customized query workflows combining static workflows and agentic research with pre-made components like search tools, MCP integrations, and LLMs) and LMUnit (a specialized evaluation model for natural language unit tests built on Meta Llama 3). The RAG Component APIs expose individual building blocks (Parse, Rerank, Generate, LMUnit) for developers who want to integrate Contextual AI capabilities directly. Pre-built Agent Composer templates (Basic Search, Agentic Search, Device Log Analysis, Deep Research) accelerate deployment, while the open-source datastore-sync tool enables customers to keep their enterprise datastores continuously synced with documentation and websites. Together, the Contextual AI Platform, Agent Composer, LMUnit, RAG Component APIs, pre-built templates, and the Grounded Language Model (built on Llama 3.1 70B) form a complete enterprise RAG and agentic AI stack.
Differentiator
Problem solved
Functional benefit
Brands
- Agent Composer: A platform for building production-ready AI agents that automate knowledge-intensive work in technically demanding industries such as aerospace and semiconductor manufacturing, launched in January 2026.
- LMUnit
Products and services
- Contextual AI Platform Unified context engineering platform organized around a three-layer architecture (Data sources, Context layer, Intelligence layer) that enables enterprise customers in advanced industries (semiconductors, aerospace, manufacturing, financial services, legal) to build production-grade AI agents that reason over technical documentation, specifications, and institutional knowledge.
- Agent Composer Framework for building customized AI agent workflows by assembling pre-made components (search tools, third-party API/MCP integrations, and various LLMs) into computational graphs. Supports hybrid agentic behavior combining static workflows with dynamic AgenticResearchStep loops and is targeted at engineers in technically demanding industries building production-ready AI agents.
- LMUnit Specialized language model and component API for evaluating natural language unit tests of LLM and agent outputs. Takes a query, a response, and a unit test as inputs and returns a continuous score (1-5) indicating how well the response satisfies the unit test criteria, enabling automated CI/CD testing of LLM applications.
- RAG Component APIs Component-level APIs that expose the Contextual AI platform's individual building blocks (Parse, Rerank, Generate, LMUnit) so developers can integrate specific capabilities (parsing, reranking, generation, evaluation) into their own applications without adopting the full Agent Composer framework.
- Grounded Language Model Contextual AI's purpose-built enterprise foundation model based on Meta's Llama 3.1 70B and hosted on Google Cloud infrastructure, engineered to ground responses in retrieved enterprise context. Achieved the highest performance on the FACTS Grounded benchmark for hallucination-resistant AI and is used to power the platform's enterprise RAG capabilities.
Quantifiable outcome
- 70% TCO savings
- +9 more outcomes
Companies that use Contextual AI
Customer profileNamed customers7 records
Segments6 records
Ideal customer profiles3 records
Contextual AI technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- Yes
- API docs
- API detail
Core technology
AI maturity
App detail
Integration11 records
AI capability12 records
Feature9 records
Contextual AI partnerships and signals
Strategic signalPartnerships
Seven partnerships are on record, tiered flagship — major licensing + talent deal, core — foundation model partner, flagship — infrastructure and marketplace partner, core integration partner, flagship — research co-development partner, core infrastructure partner and core — subprocessor for cloud hosting.
- Google DeepMindflagship — major licensing + talent dealGoogle DeepMind agreed to recruit more than 20 researchers from Contextual AI and license its technology for $80M–$90M. Contextual AI co-founder and CEO Douwe Kiela was among those joining Google DeepMind. Part of Alphabet's strategy to acquire AI talent without formal acquisitions (similar to past Windsurf and Character.AI deals).
- Meta (Llama)core — foundation model partnerContextual AI built its Grounded Language Model on Meta's Llama 3.1 70B open-source foundation model, achieving the highest performance on the FACTS grounded benchmark for hallucination-resistant AI. Meta Llama is incorporated into Third-Party Terms in the company's Terms of Use.
- Google Cloudflagship — infrastructure and marketplace partnerContextual AI built its enterprise AI platform on Google Cloud infrastructure using Meta's Llama open-source models. Self-deployment of Contextual AI's proprietary model into customer VPCs is enabled via Google Cloud Vertex AI Model Garden (alongside AI21 Labs, Mistral AI, etc.). Google Cloud also published a case study on Contextual AI. Relationship is Mutual (co-marketing + infrastructure marketplace).
- CircleCIcore integration partnerCo-published developer guide showing how to integrate LMUnit natural language unit tests into CircleCI pipelines for CI/CD testing of LLM applications; references a joint production example GitHub repo (CircleCI-Public/lmunit-tutorial).
- Ai2 (Allen Institute for AI)flagship — research co-development partnerCo-developed OLMoE, a 100% open-source Mixture-of-Experts LLM, with Ai2. Joint research and open-source release signals deep strategic alignment in the open-model research community.
- WEKAcore infrastructure partnerWEKA powers Contextual AI's production-ready enterprise AI solutions on Google Cloud, helping eliminate chatbot hallucinations with high-throughput data infrastructure for retrieval workloads. Joint press releases in Blocks and Files and PR Newswire.
- Google LLCcore — subprocessor for cloud hostingListed in the Data Processing Agreement as a Subprocessor — Cloud Service Provider hosting Customer Personal Data processed by the Services.
Scale indicators13 records
Recent moves6 records
Expansion highlights6 records
Contextual AI competitors and assessment
Company assessmentDirect peers
- Glean: Glean provides enterprise AI search and agentic assistants that ground responses in internal company data across documents, tickets, and wikis. It is the most direct competitor to Contextual AI's enterprise RAG and agent platform, targeting similar knowledge-worker use cases with comparable deployment models.
- Hebbia: Hebbia builds AI knowledge workers for financial services and professional services firms that analyze large document sets with verifiable citations. It overlaps directly with Contextual AI's document analysis, compliance research, and data room extraction use cases.
- Vectara: Vectara offers a RAG-as-a-service platform with grounding-focused APIs for hallucination-resistant enterprise search. It is a direct competitor in the enterprise RAG platform layer that Contextual AI addresses with its Unified Context Layer and Agent Composer.
- Writer: Writer delivers enterprise generative AI platforms with domain-specific agents and knowledge grounding for regulated industries. It competes with Contextual AI in financial services and other verticals where enterprise-grade grounded AI is required.
- Cohere: Cohere provides enterprise foundation models and retrieval-augmented generation tooling focused on private deployments and compliance. It is a direct competitor in the enterprise LLM/RAG category where Contextual AI also competes.
Emerging players
- Pinecone: Pinecone is a managed vector database that powers retrieval for RAG applications across the enterprise stack. While not a direct agent platform competitor, Pinecone is a complementary infrastructure layer that Contextual AI's component APIs and customers may use interchangeably.
- LlamaIndex: LlamaIndex provides an open-source framework for building RAG and agentic applications over enterprise data. It is an emerging alternative for technical buyers evaluating Contextual AI's Agent Composer for custom workflow orchestration.
- LangChain: LangChain offers an open-source framework and LangGraph platform for building LLM applications with retrieval, tool use, and agents. It overlaps with Agent Composer's developer-focused agent orchestration capabilities.
Broad incumbents
- Microsoft (Copilot / Azure AI): Microsoft bundles retrieval-augmented generation and agentic capabilities into Microsoft 365 Copilot and Azure AI Foundry, serving the same enterprise buyers that Contextual AI targets. As a broad incumbent, Microsoft competes on distribution and integrated productivity workflows.
- Google (Vertex AI / Gemini): Google Cloud's Vertex AI and Gemini provide grounded search, agentic APIs, and the Vertex AI Model Garden where Contextual AI itself is listed. Google is simultaneously a hyperscale competitor in enterprise RAG and a key infrastructure and licensing partner.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat6 records
Key risks5 records
Key highlights6 records
Customer concentration
Contextual AI social profiles
Digital presenceContextual AI compliance and trust
Trust signalCompliance5 records
Contextual AI financial estimates
Financial estimateRevenue estimate
Valuation estimate
Contextual AI leadership team
Management profileNumber of profiles
Profiles1 record
Contextual AI funding detail
Funding detailFunding overview
Funding rounds2 records
Investors10 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Contextual AI M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Contextual AI
What does Contextual AI do?
Contextual AI builds an enterprise retrieval-augmented generation (RAG 2.0) platform organized around a Unified Context Layer that combines retrieval, grounding, and agent orchestration to power production-grade AI agents. Its core products include the Contextual AI Platform, Agent Composer (a workflow framework for assembling customized query pipelines with search tools, MCP integrations, and LLMs), LMUnit (a specialized evaluation model for natural language unit tests), and the RAG Component APIs (Parse, Rerank, Generate, LMUnit). The company targets technically demanding industries (semiconductors, aerospace, manufacturing, financial services, legal) and ships pre-built templates such as Basic Search, Agentic Search, Device Log Analysis, and Deep Research.
Is Contextual AI a public or private company?
Contextual AI is a private company. It is classified as venture growth investor backed and is currently operating.
When was Contextual AI founded?
Contextual AI was founded in 2023. It employs 11 to 50 people.
Where is Contextual AI based?
Contextual AI is headquartered in Mountain View, United States, in the North America region.
How does Contextual AI make money?
Five revenue lines are on record. Platform subscription (SaaS) is the primary driver. The others are usage-based component APIs (LMUnit, Parse, Rerank, Generate), marketplace / cloud marketplace sales, technology licensing and professional services & enterprise onboarding.
Who are Contextual AI's main competitors?
Direct peers on record are Glean, Hebbia, Vectara, Writer and Cohere. Emerging players are Pinecone, LlamaIndex and LangChain. Broad incumbents are Microsoft (Copilot / Azure AI) and Google (Vertex AI / Gemini).
Does Contextual AI have an API?
Yes. Contextual AI offers public APIs including the /lmunit Component API, datastores APIs (list-datastores), and an Agent Composer execution API (/query/acl) that lets developers build customized query workflows by assembling pre-made components such as search tools, third-party API/MCP integrations, and various LLMs. The Services include access to API documentation, ability to create datastores and Customer Applications. A Python SDK is available (contextual-client). Subprocessor integrations include Auth0 (authentication), Google Cloud (cloud service provider), Sentry (error monitoring), Pylon and Slack (customer support). MCP servers are supported via the MCPClientStep node in Agent Composer workflows. External API integrations are supported via WebhookStep. Developer documentation is at docs.contextual.ai.
What industry is Contextual AI in?
Contextual AI's product category is Enterprise AI Platform / Context Engineering Software. Its primary akta.pro industry code is HDAEANAD, LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG), with a secondary code of HDAAACAE, Retrieval-Augmented Generation (RAG), Vector Databases & Knowledge Grounding. Its NAICS code is 5132 and its SIC code is 7372.