Late-stage private-company decisions live or die on four things. These are the four pillars that any institutional-grade decision surface must satisfy. Arcanis is built around those four.
| Transaction tape | Internal team model | Arcanis | |
|---|---|---|---|
| Data | Real prints. Strong signal on covered names. | Sourced by the analyst, not standardized across the institution. | Source-traced ingestion. Every input carries a full provenance record. |
| Methodology | Not the tape's job. It reports prices, not methodology. | Built deal by deal. Consistent within a team, not across one. | Encoded, deterministic. Same inputs produce the same outputs. |
| Output | A reference price and bid-ask depth. | Inspectable internally. Harder to defend in front of an LPAC. | Inspectable Excel. Independently-priced scenarios with configurable weights. |
Generative AI is great at speed and synthesis, and we use it where it helps. The core pricing methodology is encoded, deterministic, and citable. That is what the institutional review chain requires.
A range of fair-value outcomes built from orthogonal scenarios with configurable weights. Buyer and seller see the same model, weight it differently, and reach prices they can both defend.
A structured, sharable memo built for the four decisions your team actually makes: price, compare, sign off, negotiate.
One live page per company. Multiple memos with different views, the full Excel model, a copilot on the data lake, and live market offers when you need them. White-label it as the embedded surface inside your platform.
Every cell open. Every assumption configurable, including scenario weights. Change the Baseline, swap in your own risks and factors, regenerate the memo from your version, share it with your name on it.
I spent 20 years building and breaking systems in top telecoms. After growing a corporate business from $150M to $300M, I started investing and building funds in private equity and venture, where I kept seeing the same problem. Every fund rebuilds the same research from scratch. Every fund reaches different answers from broadly similar inputs. None of it is auditable in the way an institutional buyer needs.
So we built Arcanis. First as an internal tool for our own fund: our analysts use it every day to price real deals. Now we are opening it to the platforms competing to host the institutional decision surface in this market. Tape products, marketplaces, brokers, banks, secondary funds, and the institutions that price what they hold.
Embed the decision surface wherever attention already flows:
We meet you where you work.
Drop scenario pricing, memos, or full Company Hubs into your existing UI as branded widgets. Your users see your brand; you get the research engine.
Run a private-branded Arcanis instance for your platform or fund. Your domain, your design system, your client access controls.
Push price ranges, key signals, and fresh memo updates into your listings, CRM, IC dashboards, or LP-reporting stack as soon as the data lake updates.
