Every claim traceable. Every source graded. Every decision auditable. Starting with due diligence — expanding to portfolio reporting.
Every step is defensible. The sum is dangerous.
Deck: "$1.8M in signed LOIs"
AI: "Strong commercial traction"
IC: "$1.8M revenue validates demand"
Reality: $0 collected. LOIs are non-binding. Two signers lack budget authority.
Deck: "50-patient pilot showed 87% sensitivity"
AI: "Clinical data demonstrates 87% sensitivity"
IC: "Validated clinical performance at 87%"
Reality: Not an RCT. No biostatistician. Not registered. PI holds 8% equity.
Deck: "CMS created new CPT code for category"
AI: "Favorable reimbursement with CPT code"
IC: "Clear reimbursement pathway established"
Reality: Category code exists. No product-specific coverage decision. 3 MACs have denied similar tech.
Deck: "3 provisional patents filed"
AI: "Patent-protected technology portfolio"
IC: "Strong IP moat with patent protection"
Reality: Provisionals expire in 8 months. Prior art overlap. No FTO opinion exists.
Professional-looking wrongness that passes review because it looks checked.
AI can produce more analysis than you can possibly use. The bottleneck isn't generation — it's verification. Without structure, you review everything manually or miss errors.
Nobody lies. But each summary compresses uncertainty, drops qualifiers, and upgrades confidence. By the IC memo, caveats are gone.
The old guarantee was reputation-based. In AI-assisted work, 'reviewed it' might mean 'prompted and spot-checked.' You need verification infrastructure, not trust.
Structure that makes AI outputs auditable, traceable, and verifiable.
Lane A: Fast screening — explicitly labeled 'UNVERIFIED.'
Lane B: Rigorous verification with human review at every gate.
Every claim is tied to where it came from: 'Deck slide 8' or 'FDA database K231847.' No floating assertions. Hallucinations become immediately visible.
Grade A = Verified against authoritative source (FDA, audited financials). Grade C = Self-reported (deck claim). Combined with source quality for full confidence picture.
Analysts review claims at Gates 1, 2, and 3. AI extracts and organizes; humans verify and decide. The IC-Ready Rule: Verified OR labeled risk with owner. No Option 3.
What changes when you implement ProfitCopilot.
| Without ProfitCopilot | With ProfitCopilot |
|---|---|
| "The deck said so" becomes fact | Every claim traced to source with page anchor |
| Unverified AI outputs look like verified work | Lane A explicitly labeled "UNVERIFIED" |
| Quality = who touched it (reputation) | Quality = what was verified (Evidence Ledger) |
| Gaps hidden or forgotten | Gaps documented with owners and mitigation |
| Can't answer "why did we believe this?" later | Full audit trail for every claim decision |
| Each analyst figures it out independently | Institutional verification workflows |
AI extracts. Humans verify. IC sees the truth.
Upload pitch decks, data room documents, clinical reports. AI converts to markdown with page anchors preserved.
Claude extracts factual claims with source anchors. Labeled 'UNVERIFIED' — for screening, not decisions.
Analysts review claims, assign tiers (1 = IC-critical), flag issues. Tier-1 claims enter the verification queue.
Lane B: Verify against authoritative sources. Grade evidence. The Evidence Ledger shows IC what's verified and what's risk.
Starting with due diligence. Expanding across the investment lifecycle.
Extract claims from pitch decks. Verify against authoritative sources. Generate IC-ready evidence ledgers.
Available NowPortfolio companies submit quarterly updates through the same claim schema. Board decks with built-in provenance.
Coming SoonAggregate portfolio company data into LP reports. Full chain of custody from company claim to LP deck.
On RoadmapBuilt for NDA-protected documents and SOC2 compliance.
Start with due diligence. Expand as your needs grow.
Join the WaitlistProfitCopilot was built by a VC Fund Manager and a Family Office financial executive — people who've sat in IC meetings and asked "where did this number come from?" and have seen that problem compound with GenAI.
We built the tool we wished we had.