A custom multi-agent team for Investment Proposal Analysis & Optimization. Specialist agents do not just pass notes forward. They collaborate through a living Diligence Workspace: a claim ledger, evidence graph, contradiction register, source-coverage map, diligence-request queue, and human-gated audit trail. It feels like magic because the science is explicit.
The agents stay inside a deterministic, auditable graph. The magic happens in the shared workspace: every claim is tracked, every source is linked, every contradiction becomes visible, and later agents adjust their own conclusions when earlier specialists expose a gap. The latest diligence packs make missing proof visible instead of hiding it in polished prose.
Think of it as a living laboratory notebook for the investment. Intake writes the hypotheses. Research and technical validation attach evidence. Regulatory and red-team register risk. Competitive mapping records substitutes and do-nothing alternatives. Financial diligence exposes source inventory, scenarios, model integrity, cash/runway gaps, and PBC requests. The memo synthesizer sees the whole record.
Every material founder claim becomes a tracked object with status: supported, unsupported, conflicted, or founder-only.
Findings are linked back to claims, graded A-D, and tied to citations so the memo can be traced to source material.
When a technical, regulatory, or financial result challenges a claim, the conflict becomes explicit instead of disappearing in prose.
Downstream agents adapt. A mechanism gap can raise financial risk. Missing financial proof becomes a request, not a fake model.
The system now exposes how each stage reached its conclusion: what sources were available, what was missing, which assumptions matter, and what must be requested before committee review.
Deep research returns a plan, source coverage, cited findings, market-size support, and open diligence questions when evidence is missing.
Competitive analysis separates direct competitors, substitutes, incumbents, adjacent players, and the do-nothing/current-workflow alternative.
Technical diligence tracks readiness level, proof requirements, validation experiments, scalability risk, and prior-art or literature gaps.
Financial review shows data inventory, driver assumptions, base/bear/bull scenarios, model integrity, QoE/NWC flags, debt-like items, valuation support, and PBC requests.
Rigorous, independent scrutiny is bottlenecked on scarce expert attention. A great analyst is expensive, biased by the same deal heat as everyone in the room, and can't cover fusion, gene therapy, and novel silicon with equal depth.
"I get fifty decks a month and I have to say yes to two. Half are in fields where I can't independently check the technical or regulatory claims. I'm anchored by whoever pitched me last, and the one deal I get wrong wipes out the returns on the ten I get right. My diligence is inconsistent, it lives in my head, and I can't defend it to my LPs."
— The stretched investment partnerNot a chatbot. Not a free-roaming agent swarm. A directed graph of domain experts that read and write the same workspace. No single agent "decides"; the recommendation emerges from claim-linked evidence, explicit contradictions, risk adjustments, and an adversarial red-team pass.
Parses decks, models, and data rooms — PDF, DOCX, XLSX, PPTX, CSV — into clean text and table previews, then writes a source-processing note into the workspace.
Extracts the thesis, the material claims, and the capital ask — then seeds the claim ledger and opens diligence questions for missing evidence.
Builds a research plan, reports source coverage, corroborates or refutes claims, and carries open questions forward when evidence is missing.
Profiles direct competitors, substitutes, incumbents, adjacent players, and the do-nothing alternative, then surfaces moat threats and white space.
Separates prototype feasibility from commercial scale, assigns readiness where possible, and lists proof requirements, validation experiments, and prior-art gaps.
Identifies applicable regimes — FDA pathways, SEC, GDPR, export controls — and writes regulatory risk into the same ledger the model and memo read.
Creates a financial diligence pack: source inventory, driver assumptions, scenario table, model integrity checks, QoE/NWC flags, valuation support, and diligence requests.
Runs after the model and attacks the thesis, turning hidden dependencies and kill criteria into workspace questions before the final memo.
Assembles the memo from the whole workspace and constrains overconfident recommendations when contradictions or unsupported claims remain unresolved.
The pipeline pauses at every material decision and waits for an explicit human decision. Your economics and finance experts calibrate assumptions, weigh the red-team, and own the final call — the agents do the heavy lifting in between, with a workspace snapshot visible at every gate. At each gate, humans can chat with the system, add new evidence or management context, and correct agent outputs before the next specialist acts. The result is not automation replacing judgment; it is a scientific collaboration loop with humans inside the circuit.
The value isn't the LLM call — it's the discipline around it.
Every finding can link back to a material claim, carry an A-D evidence grade, and preserve citations. Unsourced assertions are marked, not laundered into proof.
Research, competitive, technical, and financial stages show source coverage, missing data, proof requirements, and requests before synthesis.
When technical, regulatory, financial, or red-team work challenges a claim, the conflict is registered and carried into the memo instead of being averaged away.
Every finding, grade, contradiction, adjustment, and gate decision is reconstructable. The memo is the polished surface of a defensible scientific record.
Engagements range from a targeted red-team review to a full diligence workspace and memo, tailored to your sector, thesis, and investment process. Tell us about the proposal and we'll scope it with you.
Contact SimQuant LLC or email [email protected]