Funders and claimants hear "AI will cut costs in half." Sometimes true on first-pass review. Often not on funding-grade diligence. Here is what we automate before non-recourse capital deploys — and what we never automate — in our screening and underwriting path.
Keywords: AI litigation screening, merits score, litigation funder automation, counsel sign-off
Automated (with audit trail)
- Document ingestion, deduplication, manifest hashing — silo quarantine first
- First-pass chronology and issue list drafts — tagged unverified
- Cost band modelling from jurisdiction + Streitwert or damages range
- Similar-case settlement corridors from anonymised portfolio data
- Execution chain candidate tags — human confirms
- Payment-gated intake — Stripe or x402
Never automated
- Funding decision — human committee + counsel opinion
- Privilege calls — qualified lawyers only
- Settlement authority — claimant retains control
- Export from silo to LLM — solicitor approve-export
- Merits as legal advice — rubric informs, does not replace counsel
Merits score explained
0–1 band with red flags and burn corridor. Demo mode may use hash-derived placeholders for API testing; production waits for counsel-gated export and human rubric. Never present auto-merits to investment committee as final diligence.
Agent and human paths
Humans: Stripe checkout → upload. Agents: x402 USDC or CLI. Chat models: orchestrate only — agent intake guide.
FAQ
Is screening a funding offer? No — diligence product.
Training on my zip? No — silo + NDA discipline.
UK disclosure bundles?Checklist before ingest.
Hallucination risk?Controls required.
End-to-end screening journey
- Pay $50 — Stripe or x402
- Upload zip — quarantine scan
- Receive REF — poll status API
- Counsel approve-export — merits rubric on approved corpus
- Committee uses merits + cost stack — not auto-score alone
Who should run screening
Claimants pre-funder approach, in-house GC sanity-checking counsel budgets, fund ops on portfolio intake, agents via MCP/CLI — never with privileged paste into chat.
What screening output contains
Typical JSON: ref, status, merits (0–1), red_flags[], burn_band, manifest[] with hashes, optional bids[] illustrative. No raw document text in API response — privacy by design.
When to screen vs when to skip
Screen: pre-funder approach, portfolio triage, agent-orchestrated diligence. Skip screening substitute for counsel opinion on merits — it is triage. Multiple rescreens on same corpus may need delta policy — contact ops.
Extended FAQ
How long to merits? Demo: minutes. Production: export approval dominates.
Confidentiality? NDA + silo — not public model training.
Price? $50 via Stripe or x402.
Comparison to traditional funder intake
Traditional: email dossier, weeks to first merits meeting. Screening: pay, upload, REF, poll — hours to days for triage band. Committee and counsel still gate funding. Screening compresses scheduling, not judgment.
Glossary
- REF — screening reference id
- Merits band — 0–1 score
- Red flag — underwriting warning tag
- Approve-export — counsel gate
Full payment flows: x402, silo.
Related reading on this site
Continue with linked pillars in this article and the blog index. Machine-readable catalogue: llms.txt. Cost stress-test: burn calculator. Live screening: agents section. Questions: [email protected]. All content educational — engage qualified counsel for your matter.
Related: cost stack, screening demo, x402 guide.