HTTP 200 verified twice
Finding your next stop…
Loading the latest directory information.
Loading the latest directory information.
Contextual AI offers an enterprise context engineering platform with a layered non-parametric memory system powering production RAG agents. Agent Composer enables model-agnostic orchestration across docs, logs, web search, and APIs with SOC 2 Type II compliance.
Start here for the decision-making essentials: what Contextual AI does, who it is for, how it is accessed, and the first-party sources behind this profile.
See official pricing
Read-only public captures of Contextual AI’s homepage. Screenshots are dated, never live embeds, and open full-screen.
Short answers to the questions buyers and builders commonly ask about Contextual AI. Each answer cites the shared ledger below, where every source is listed once.
Context engineering platform for building production-grade AI agents that reason over tech · Answers are verified with sentence-level attributions and visual bounding boxes · Contextual AI Platform delivering specialized RAG agents for enterprise knowledge workflow · Includes a reranker component that can be integrated into customer RAG pipelines
The unified context layer that powers expert AI in advanced industries. Build AI agents that reason over technical documentation, specifications, and institutional knowledge
Financial analysts, wealth advisors, risk managers, and investment, corporate, and retail · Legal associates, tax professionals, management consultants, and technology consultants · Technical and R&D-focused industries including semiconductors, electronics, aerospace, man · Enterprise teams deploying AI agents who need continuous context optimization
Empower your most valuable teams, from financial analysts to wealth advisors to risk managers
Specialized RAG agents for technology and engineering teams across semiconductors, hardwar · Complex technical workflows including root-cause analysis, production planning, test code · Agentic search tasks across engineering and finance domains
AI solutions across technology & engineering
APIs and SDKs available for Python, TypeScript, and JavaScript to manage the full agent de
Integrate your existing SDKs Python TypeScript JavaScript
Broad enterprise data support including multimodal documents, structured databases and dat · Agents can take API write actions across enterprise systems and coordinate docs, logs, and
broad support for all of your enterprise data, including multimodal documents, structured databases and data warehouses, and popular SaaS applications
Flexible deployment across multi-tenant SaaS, dedicated cloud instances, or private VPC · Service is built on Google Cloud Platform (GCP) · Flexible deployment options including fully managed SaaS, virtual private cloud, or on-pre · Designed to move AI solutions from demo to production in weeks with hands-on partnership f
Flexible deployment options Choose between multi-tenant SaaS, dedicated cloud instances, or private VPC deployment on your preferred cloud platform
This profile connects the jobs Contextual AI is described as handling with its delivery model, access options and the subjects used to match it to related products in this directory.
Each fact points to a recorded source, making it easy to distinguish verified product information from claims that need checking.
HTTP 200 verified twice
Context engineering platform for production-grade AI | Contextual AI
Company is Contextual AI, Inc. headquartered at 150 W Evelyn Ave #200, Mountain View, CA 9 · Platform is a context engineering layer for production-grade AI agents reasoning over tech · Layered non-parametric memory splits working, procedural, semantic, and behavioral memory
Contextual AI
150 W Evelyn Ave, #200, Mountain View, CA 94041, US
Context engineering platform for building production-grade AI agents that reason over technical documentation, specifications, and institutional knowledge
Agent Composer for defining and configuring specialized agents and workflows via pre-built agents, natural language prompts, or a visual editor
Flexible deployment across multi-tenant SaaS, dedicated cloud instances, or private VPC
Service is built on Google Cloud Platform (GCP)
SOC 2 Type II certified
Industry-standard TLS for data in transit and AES encryption for data at rest, with multi-tenant data isolation
Enterprise-grade SSO supporting social login and SAML/OIDC, plus role-based access control
A concise view of the jobs, capabilities and integrations described in the recorded product sources.
Documented product formats, platforms and official distribution destinations. Availability can vary by region and plan.
A concise history of software releases and material product changes. Events appear only when a dated source supports what changed.
Showing the newest updates and meaningful milestones. Open an entry for its summary and source.
Technical post explaining Contextual AI's approach to memory systems for RAG 2.0 agents, framing memory as essential for multi-turn, enterprise production work that requires the agent to retain domain, tool-use, and user-feedback context.
View source [8]Article sharing production lessons from deploying Agentic Context Engineering (ACE) on enterprise agentic-search workloads, identifying feedback quality and data efficiency as the two blockers that determine whether ACE improves or regresses an agent.
View source [9]Article contrasting semantic layers (which make structured data understandable to BI tools) with Contextual AI's context layer (which makes structured and unstructured enterprise data usable by AI agents), positioning the context layer as necessary for AI reas
View source [12]Research findings on improving search-agent research phases via two design axes—search tool configuration and planner training with an efficiency reward (CLP)—reporting up to 60.7% accuracy on BrowseComp-Plus and proposing the Cumulative Evidence Recall (CER-C
View source [11]Facts, answers, structured details, milestones and primary resource links cite this shared ledger. Each external page appears once; release tags from the same GitHub project are grouped under one release history.
These tools share a workflow, capability or audience with Contextual AI. They may complement it rather than replace it, and are not presented as integrations or endorsements.
APIs and SDKs available for Python, TypeScript, and JavaScript to manage the full agent development lifecycle
Active bug bounty program offering rewards to identify and remediate platform vulnerabilities
Twitter/X: https://x.com/contextualai; LinkedIn: https://www.linkedin.com/company/contextualai; YouTube: https://www.youtube.com/@contextualai
Answers are verified with sentence-level attributions and visual bounding boxes
Context engineering / enterprise AI agent platform
Contextual AI, Inc.
Contextual AI Platform delivering specialized RAG agents for enterprise knowledge workflows
Includes a reranker component that can be integrated into customer RAG pipelines
Supports fine tuning and feedback learning for custom language models
Financial analysts, wealth advisors, risk managers, and investment, corporate, and retail banking teams
Legal associates, tax professionals, management consultants, and technology consultants
Flexible deployment options including fully managed SaaS, virtual private cloud, or on-premises
Complies with GDPR, CCPA/CPRA, Colorado Privacy Act, Connecticut Data Privacy Act, and Directive 2002/58/EC, with EU/UK/Swiss transfers covered by Standard Contractual Clauses
Active on X (x.com/contextualai), LinkedIn (linkedin.com/company/contextualai), and YouTube (youtube.com/@contextualai)
Contextual AI
Context-aware AI platform that understands enterprise data, workflows, and edge cases via specialized RAG agents
Platform outperforms competing enterprise AI systems built with leading frontier models including Claude Sonnet and ChatGPT
Specialized RAG agents for technology and engineering teams across semiconductors, hardware, software, telecom, cybersecurity, digital media, ecommerce, and cloud infrastructure
Broad enterprise data support including multimodal documents, structured databases and data warehouses, and popular SaaS applications
Comprehensive security features and capabilities to safeguard data, enforce proper access permissions, and maintain regulatory compliance
Designed to move AI solutions from demo to production in weeks with hands-on partnership from AI experts
Layered non-parametric memory system for RAG 2.0 agents, splitting working, procedural, semantic, and behavioral memory into separate layers
Uses ACE-style optimization and GEPA prompt optimization along with LMUnit self-reflection for memory validation and continuous improvement
State-of-the-art AI models developed by an applied research team for production enterprise AI
Official profiles on Twitter/X (@contextualai), LinkedIn (/company/contextualai), and YouTube (@contextualai)
Contextual AI
Mountain View, CA, US (150 W Evelyn Ave #200, 94041)
Unified context layer specialized for domain-specific tasks in technical industries
