TableFlow Due Diligence

Run due diligence on TableFlow: check compliance and get alerts when suppliers change.

United States · tableflow.com · 5 vendors

TableFlow is an AI-powered platform that automates complex data tasks, including document processing and data workflows. It enables businesses to extract, transform, and validate unstructured data from various sources like PDFs, spreadsheets, and images. The company aims to reduce manual effort, accelerate processing speed, and improve data accuracy for its users.

Resilience scores

Technology vendors

Services catalogue

1 service in catalogue across 1 category; runs on 5 sub-vendors.

Insights

Last updated 2026-05-21 · revision 2

5 direct vendors, 95 subvendors

Direct vendors by controlling owner country (sample)

Subvendors by controlling owner country (sample)

Compliance

3 in-scope frameworks identified; showing 3.

GDPR (source) — No public evidence

Evidence: https://tableflow.com/privacy, https://tableflow.com/security

SOC 2 (source) — Evidence found

Evidence: https://tableflow.com/security

ISO 27001 (source) — No public evidence

Evidence: https://tableflow.com/security

Financials

Three-year financials

Financial Resilience Score: 6/10

TableFlow (Portola Labs, Inc.) is an early-stage, venture-backed private company with no publicly disclosed financial statements. Its resilience is therefore assessed qualitatively. The company benefits from strong institutional investor backing, including Y Combinator, BOND (Mary Meeker's firm), Precursor Ventures, Nomad Capital, and TwentyTwo Ventures, which provides funding runway and credibility. Product-market fit signals are positive, with marquee customers across multiple verticals and published case studies demonstrating measurable customer value (e.g., 90% manual-work reduction, 300% volume increases at Ghost). However, as a seed/early Series A stage company, TableFlow likely operates unprofitably and depends on continued venture funding rather than operating cash flow. The intelligent document processing market is highly competitive, with established players (Conexiom, Rossum, Esker, Hyperscience) and hyperscaler offerings (AWS Textract, Google Document AI, Azure AI Document Intelligence). Additionally, reliance on third-party LLMs creates gross-margin exposure to inference pricing. Customer concentration risk is typical at this stage, and the lack of public financial disclosure limits external verification of burn rate or ARR.

Key strengths: Strong investor backing including Y Combinator and BOND, Marquee enterprise customers (Ghost, True Classic, Resend, Homebot, GCG), SOC 2 Type II certification, High product velocity with V2 platform launched September 2025, Multi-LLM routing across Anthropic, Bedrock, Mistral, Gemini, Enterprise integrations with NetSuite, SAP, Salesforce, Capital-efficient two-founder engineering-led team, Short customer go-live cycles (~2 weeks)

Risk factors: Early-stage company likely unprofitable, dependent on VC funding, Highly competitive IDP market with established incumbents and hyperscalers, LLM dependency exposes gross margins to inference pricing changes, Customer concentration risk typical of seed-stage startups, No public financial disclosure limits transparency, Small team size relative to enterprise-focused competitors

Revenue by geography

Revenue by product/service

Workforce by country

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