Unstruk Data, Inc. Unclaimed
Unstruk Data, Inc. provides an API-first platform for enterprise knowledge graphs and AI-enabled workflows.
Unstruk Data, Inc. is a technology company that builds platforms for enterprise knowledge management and AI-enabled workflows. The organization focuses on connecting diverse data sources—across documents, emails, calendars, CRM and collaboration tools—into a unified knowledge graph and memory. Its flagship platform enables ingestion, extraction, enrichment, and retrieval of operational content, empowering teams to build grounded, context-aware AI agents and applications that improve decision-making, collaboration, and productivity.
To help organizations unlock trusted, searchable context from fragmented data and enable AI-driven agents to reason over it to automate knowledge work.
What we offer
Graphlit Platform
Transform diverse content into actionable insights with the Graphlit Platform for AI solutions.
www.graphlit.com/Market segments
Market size by segment
Growth potential (CAGR)
Enterprise knowledge management
Capabilities to author, maintain, analyze, and ground knowledge used by AI and service workflows, including gap analysis, content recommendations, and article‑level performance insights.
Retrieval-augmented generation platforms
Capabilities that integrate enterprise data retrieval with large language models to provide contextually accurate, up-to-date responses using RAG, vector storage, and secure enterprise data connectors.
Enterprise cognitive search
AI‑powered search and retrieval capabilities that surface contextual, personalized, and RAG‑enabled answers across multiple enterprise systems and content sources.
Content ingestion and connector orchestration
Connectors, web crawling, and ETL workflows that consolidate content from SaaS apps, email, calendars, web, and documents into structured, RAG-ready formats for downstream AI use.
More information about our offering
Graphlit Platform
Graphlit Platform is an API‑first knowledge management and AI workflow platform. It ingests content from more than 30 data sources, extracts structured data, enriches it with summaries, and retrieves grounded context to power AI agents and applications. Built around a persistent knowledge graph and memory, it connects documents, emails, calendars, CRM and collaboration tools, and delivers grounded, citeable results across connected tools. With a managed RAG pipeline, semantic search, and scalable production features, Graphlit supports building, deploying, and governing context‑aware AI solutions in enterprise environments.
- Unify Context Across SourcesIngest data seamlessly from multiple sources like PDFs, web pages, and databases to create a comprehensive view of your information.
- Persistent Memory ManagementCreate a connected knowledge graph that retains context, enabling effective retrieval and insights across projects.
- Real-Time Preview and CitationGenerate responses based on real-time data retrieval, improving the relevance and accuracy of the information presented.
- Automatically Extract EntitiesEnhance insights by automatically identifying key entities within your documents, facilitating better decision-making.
- Advanced Search CapabilitiesUtilize semantic search to enhance content accessibility, allowing users to find relevant information quickly.
- Streamlined Document HandlingTransform PDFs and other document types into searchable formats, ready for intelligent retrieval in applications.
- Scalable Enterprise DeploymentDeploy and manage applications in a multi-tenant architecture, ensuring security and efficient resource management.
- Structured Content TransformationFacilitate a streamlined workflow that elevates raw content into actionable insights through systematic processing.
- Enhanced Content AccessibilityUtilize advanced web crawling techniques to enhance the quality and usability of extracted data.
References
Methodology and sourcing behind the figures shown above.
Enterprise knowledge management
Estimates derive from industry reports in the search results for the knowledge-management / enterprise KM software market. Fortune Business Insights reports a market value of USD 23.2B in 2025 (CAGR 13.8%). MarketResearchFuture gives a smaller 2025 base (USD 14.56B) and a higher software-focused CAGR (16.92%). A LinkedIn summary of an enterprise‑KM report indicates a lower 10.3% CAGR for enterprise knowledge management specifically. A much larger BusinessResearchInsights figure (USD 931.26B, CAGR 18.12%) appears to use a much broader KM definition. For the user’s enterprise knowledge management segment (authoring, maintenance, analytics, grounding for AI/workflows), I adopt the software‑market focused 2025 base (Fortune) and a midpoint growth potential (~15% CAGR) between the cited software estimates (≈10–17%), adjusting downward from the very large broad-market figure.
- Global market size 2025: USD 23.2 billion; CAGR (2025–2034): 13.8%.
- Market reached an estimated USD 14.56 billion in 2025; projected to USD 70.01 billion by 2035, CAGR 16.92%.
- Projected CAGR of 10.3% from 2026 to 2033 for Enterprise Knowledge Management System market.
- Knowledge Management Market valued at USD 931.26 Billion in 2026; projected to USD 4,168.52 Billion by 2035 at CAGR 18.12%.
Retrieval-augmented generation platforms
Primary estimate uses Precedence Research’s explicit 2025 market size and forecast (USD 1.85B in 2025; CAGR 49.12% 2025–2034). This is corroborated by AtScale’s citation of a Grand View Research estimate (~USD 1.043B in 2023) and a similar high-growth projection (44.7% to 2030), indicating strong consensus on rapid multi-year CAGR.
Enterprise cognitive search
SNSInsider directly reports the AI‑powered cognitive search market at USD 2.87B in 2024 with a 16.19% CAGR to 2032. Broader AI search and enterprise search reports (FMI, MRFR) show larger adjacent markets (USD 18.5B AI search; USD 5B enterprise search in 2024), which support treating cognitive/AI‑powered enterprise search as a smaller, high‑growth segment within the larger AI search ecosystem.
Content ingestion and connector orchestration
Estimate based on the AI orchestration platform market (Precedence Research) which reports a USD 11.1 billion market in 2025 and a 22.16% CAGR (2026–2035). Content ingestion and connector orchestration is treated as a subsegment (connectors, crawling, ETL within AI/data orchestration); assuming a reasonable share of ~20% of the overall AI orchestration market yields ~USD 2.22 billion in 2025. Growth potential aligned with the broader AI orchestration CAGR (22.16%), given rising demand for data/connector tooling for RAG and enterprise AI pipelines.
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