Contextual AI

Contextual AI is an enterprise retrieval-augmented generation (RAG) and agent platform for engineering-heavy organizations such as semiconductor, aerospace and manufacturing companies. It lets technical teams build grounded agents over manuals, specifications, logs and tickets that answer with sentence-level citations, removing the months of retrieval-pipeline plumbing most in-house RAG projects stall on.

Contextual AI was founded in 2023 by Douwe Kiela, who led the Meta AI research team that introduced retrieval-augmented generation, and Amanpreet Singh, and builds what it calls a unified context layer for enterprise AI. The platform bundles the components of a production RAG stack behind one API and UI: a document parser that infers the hierarchy of long, complex documents, an instruction-following reranker, its own Grounded Language Model (GLM, introduced March 2025 and built by fine-tuning Llama) that is trained to answer only from retrieved sources with inline attributions, and LMUnit, a model for unit-test style evaluation of responses. The enterprise platform reached general availability in January 2025. On 27 January 2026 the company launched Agent Composer, an orchestration layer on top of that context layer that adds multi-step reasoning, multi-tool coordination and a mix of dynamic agents and static workflows; teams can start from six pre-built agents (basic search, agentic search, deep research, root cause analysis, task execution and structured extraction), generate an agent from a natural-language description, or use a visual drag-and-drop builder, and the platform is model agnostic, supporting OpenAI, Anthropic and Google models alongside GLM. Named customers include Qualcomm, Advantest, ShipBob and Nvidia, and the vendor claims root-cause analysis cut from about eight hours to 20 minutes. The company raised a $20M seed (Bain Capital Ventures, 2023) and an $80M Series A led by Greycroft in August 2024. In May 2026 Google DeepMind hired more than 20 of its researchers, including Kiela, and licensed its technology in a deal reported at $80-90M; Contextual AI continues to sell the platform under interim CEO Jay Chen. It competes with enterprise search and RAG platforms such as Glean, Vectara, LlamaCloud and hyperscaler agent builders.

Category

Enterprise Search & Knowledge

Pricing

Usage-based, Contact for pricing

Target Market

CTOs, VPs of Engineering, Heads of AI, Enterprise Developers

Deployment

Cloud-first, API-based

Founded

2023

Headquarters

Mountain View, United States

Team Size

51-200

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  Agent Composer

  Orchestration layer launched January 2026 for multi-step, multi-tool agents and static workflows, so complex engineering tasks run reliably rather than as single prompts.

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  Pre-built agent templates

  Six templates including deep research, root cause analysis and structured extraction let teams start from a working agent instead of a blank canvas.

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  Grounded Language Model (GLM)

  A model fine-tuned to answer only from retrieved context with inline attributions, reducing hallucinations in enterprise answers that must be auditable.

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  Hierarchy-aware document parser

  Parses long, complex documents and infers section structure, which the vendor reports raised RAG accuracy on SEC filings from 69.2% to 84.0%.

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  Instruction-following reranker

  Reranker that accepts custom instructions such as recency or source priority, letting teams tune which retrieved passages the model sees.

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  LMUnit evaluation

  Unit-test style evaluation model that scores responses against natural-language criteria, supporting regression testing before agents go live.

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  Enterprise connectors and MCP server

  Connectors for SharePoint, OneDrive, Google Drive, Box and Confluence with entitlement enforcement, plus an MCP server for use from coding and chat tools.

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  Semiconductor root-cause analysis

  Engineers query test logs and failure histories so an investigation the vendor says took eight hours is reduced to roughly twenty minutes.

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  Technical support deflection

  Support and field engineers get cited answers from product manuals and tickets, speeding issue resolution; ShipBob reports resolving issues much faster.

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  Test code generation

  Agents read specifications and existing test suites to draft test code, turning work that took days into minutes according to customer claims.

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  Specification and compliance review

  Structured-extraction and compliance agents check documents against requirements and return cited findings reviewers can verify line by line.

Component APIs are publicly priced and metered per page parsed and per million tokens (parse $3 per 1,000 text pages, $40 multimodal; generate $3 in / $15 out per 1M tokens), with $25 of free credits at signup. VentureBeat reported self-serve Agent Composer starting at $50 per month. SSO, HIPAA, multiple workspaces and customer-VPC deployment are Enterprise-only and quote-based.

This page was written from 9 sources, 6 on domains other than contextual.ai.

1. 1.contextual.ai — pricingvendor
2. 2.contextual.ai — introducing agent composervendor
3. 3.docs.contextual.ai — llms.txt
4. 4.contextual.ai — blogvendor
5. 5.venturebeat.com — contextual ai launches agent composer to turn enterprise rag
6. 6.en.wikipedia.org — Contextual AI
7. 7.en.wikipedia.org — Douwe Kiela
8. 8.finance.yahoo.com — google deepmind hires staff contextual 194051475
9. 9.hn.algolia.com — search