Morphik

What do they actually do

Morphik is an open‑source, visual‑first search and knowledge platform for multimodal documents (PDFs, images, diagrams, videos). Teams can self‑host the open‑source core or use a hosted cloud service. Today you can ingest documents via web UI, API, or Python SDK; the system builds visual embeddings so pages, diagrams, tables, and layouts remain searchable beyond OCR text alone. It also supports entity/relationship extraction to build a queryable knowledge graph, and provides an agent that chains retrieval, graph traversal, and other tools for multi‑step research workflows (homepage/docs · getting started · ColPali/multimodal · knowledge graphs · agent).

Early users are developers and teams building AI copilots and research tools, including technical/research and regulated settings; YC notes examples ranging from space‑tech research to brokerage agents. For production, Morphik offers paid cloud tiers and enterprise options (SSO, audit logs, backups, on‑prem/BYO‑cloud; SOC2/HIPAA support on request). They publish benchmarks and evaluation code, but these are vendor‑provided and should be validated on your own documents (YC profile · pricing/enterprise · GitHub evals).

Who are their target customer(s)

• Research scientists and R&D teams working with papers, patents, and technical reports: They struggle to find specific diagrams, tables, or cross‑paper relationships buried in PDFs/images, so answering multi‑step questions requires manual reading and note‑taking (YC profile · multimodal docs).
• Developers building AI copilots or research tools: They lose time stitching OCR, vector stores, and ad‑hoc logic; assistants miss facts or hallucinate on images/complex layouts. They want an integrated, visual‑aware retrieval and agent stack (YC profile · agent/RAG-CAG).
• Compliance, legal, and healthcare teams in regulated enterprises: They need auditable extraction of obligations/entities from scanned contracts and reports, plus on‑prem/SOC2/HIPAA options before trusting a hosted service (pricing/enterprise · knowledge graphs).
• Field service and manufacturing engineers who use manuals and schematics: They need fast, exact answers tied to a specific figure or step in a diagram, not fuzzy keyword matches, to avoid delays in technical work (multimodal docs).
• Internal product/knowledge/data teams making company documents searchable: They want cross‑document relationship queries without hand‑labeling or custom pipelines, across many file types, with simple SDKs to integrate (knowledge graphs · getting started/SDK).

How would they acquire their first 10, 50, and 100 customers

• First 10: Run high‑touch pilots with YC contacts, early GitHub users, and known R&D teams, offering free time‑boxed trials with engineering support to validate visual retrieval on their documents; turn wins into detailed case studies and paid extensions.
• First 50: Ship starter templates, one‑click cloud onboarding, and SDK demos so teams can evaluate in an afternoon; drive discovery via targeted how‑tos, conference sponsorships, and outreach to convert trial users into paying teams.
• First 100: Hire a small sales team to close mid‑market deals in legal/healthcare/manufacturing with on‑prem trials and compliance checklists; add channel partners (DMS vendors/SIs) and use early references to shorten procurement.

What is the rough total addressable market

Top-down context:

Morphik sits at the intersection of knowledge‑management software, enterprise search, and intelligent document processing (Document AI). Conservative 2024 estimates for these markets sum to roughly USD 25–30B, with strong growth expected (KM · enterprise search · IDP/Document AI).

Bottom-up calculation:

Using published 2024 figures: KM ~$20.15B + enterprise search ~$4.9–6.1B + IDP/Document AI ~$2.3B ≈ $25–30B combined. Forecasts indicate continued growth across all three segments (KM · enterprise search · IDP).

Assumptions:

• Market categories overlap; totals indicate budget footprint rather than distinct buyers.
• Morphik’s serviceable market focuses on heavy PDF/diagram workloads and regulated buyers, a subset of the aggregate.
• Estimates use conservative 2024 figures from cited reports without adjusting for overlap.

Who are some of their notable competitors

• Weaviate: Open‑source search/knowledge platform with multimodal (text+image) support and a graph‑like schema, enabling image‑aware and relationship queries; notable as a mature OSS option many teams already use (docs).
• LlamaIndex: Developer library for building document indexes and agent workflows; strong connectors and indexing abstractions, but it’s a toolkit rather than an end‑to‑end hosted visual‑first product (docs).
• Haystack (deepset): Open‑source RAG/pipeline toolkit with enterprise features and tutorials for vision+text QA; typically requires more integration work versus integrated platforms (tutorial).
• LangChain: Widely used framework for agents and tool orchestration; you supply the underlying document store, OCR, and multimodal indexing, making it complementary but not a complete retrieval product (docs).
• Qdrant: Open‑source vector database focused on fast similarity search and filtering; often paired with separate OCR/visual indexing/graph layers for end‑to‑end retrieval (overview).