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FJ Labs is one of the world's most active venture capital firms, running a deal pipeline that brings in a constant flow of investment proposals, SAFEs, convertible notes, and equity agreements. For a team operating at that volume, manually reviewing, extracting, and routing each document was not just time-consuming — it had become a genuine bottleneck in the decision-making process.
We built an end-to-end document intelligence platform that integrates directly with their existing email workflows. Every incoming document is captured automatically, analysed by AI to extract structured investment data, and routed through a multi-step approval workflow — all without any manual intervention. The investment team now has a single, always-current source of truth for every deal in the pipeline.
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The team receives a constant flow of SAFEs, convertible notes, equity agreements, and investment proposals. Manual review of each created delays and inconsistencies across the pipeline.
These are not simple forms. They contain layered legal and financial terminology, variable structures, and critical terms that need to be extracted accurately — not approximated.
After extraction, documents needed to move through a defined approval process involving multiple stakeholders, with email-based sign-off and a clear audit trail at every stage.
The investment team needed a single view of all documents, their current status, the decisions made at each stage, and the commentary from every reviewer — in one place, always up to date. —
We delivered a fully automated document intelligence platform built around three core capabilities: intelligent extraction, automated workflow routing, and a centralised deal dashboard.
Incoming documents are captured automatically through a direct Microsoft Outlook integration. As soon as a document arrives, the platform's AI layer extracts structured investment data — key terms, instrument type, company details, and financial conditions — with precision and consistency that manual review cannot reliably match.
From there, the document moves through a multi-step approval workflow automatically, with email-based stakeholder notifications and sign-off built in at every stage. The entire process runs without anyone having to initiate, track, or follow up on it.
A centralised web portal gives the investment team a real-time view of every document in the pipeline — its current status, the decisions made at each stage, and the commentary from reviewers. Role-based access ensures the right people see the right information, whether they are reviewers, admins, or super-admins. A complete web-based UI also allows the team to review documents and trigger the full workflow manually when needed.
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Incoming investment documents are captured automatically from email, with zero-friction document ingestion that requires no manual upload or filing from the team.
The platform's AI layer extracts structured investment data from complex legal and financial documents — including key terms, instrument classification, and financial conditions — accurately and consistently.
Documents move through a defined multi-step approval process automatically, with email-based stakeholder notifications and sign-off captured at each stage.
A real-time dashboard gives the investment team visibility across the entire pipeline — document status, decisions, and reviewer commentary — in a single source of truth.
Reviewers, admins, and super-admins each interact with the platform according to their defined role, keeping the workflow clean, secure, and appropriately controlled.
Every action, decision, and annotation is captured and stored, providing a complete and reliable record for compliance and future reference. —
The platform significantly reduced the time from document receipt to investment decision, eliminated manual data entry entirely, and gave the FJ Labs investment team a single source of truth for all deal flow management. What previously moved slowly through inboxes and spreadsheets now flows through a clean, automated pipeline — with every decision tracked and every document fully accounted for.
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*End of Case Study — FJ Labs*
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