Finance teams need forecasts they can defend, not forecasts they have to explain away. BYO LLM keys and audit manifests are the architecture finance actually wants — even if it never asked for them by name.
Finance is the function where "the model said so" is never an acceptable answer. Every forecast has to be defensible — to auditors, to the board, to regulators — which means every forecast needs a record.
The Corporate-Finance Lens
A finance team's AI work is judged on a different bar than a product team's: not "is it accurate enough," but "can we defend it six months later, under audit, with the records intact." The infrastructure has to match the bar — or the work doesn't ship.
- The forecast must be defensible, not just accurate.
- The records must survive the audit window, not just the demo.
- The data and keys must stay with the firm, not the vendor.
Why BYO LLM Keys
Bring-your-own keys is a finance requirement, not a technical preference. If the vendor holds the keys, the vendor holds the data flow — and the firm is defending decisions made on infrastructure it doesn't control. BYO keys keeps the data flow with the firm, which is where the defense has to live.
What the Audit Manifest Replaces
The audit manifest replaces the spreadsheet-and-email record most finance teams use to "document" AI outputs. Instead of reconstructing a decision from scattered emails six months later, the manifest is attached to the output at decision time — model, data, version, decision.
What Deino Ships
Deino is built for the finance team that has to defend every output: probabilistic forecasts with audit manifests attached, BYO LLM keys, the four invariants in the Rust workspace, free → Pro → Enterprise tiers. The platform is the unit of value, not the seat — finance buys the substrate, not a per-user tool.
Conclusion
Finance teams need forecasts they can defend. BYO keys and audit manifests are the architecture that matches the bar — your data, your keys, your records, your defense.
About FACTA
FACTA helps startups and growth-stage teams turn AI into production systems that keep running — not demos that impress once.
We design the architecture around the parts that actually break under real usage: tooling you own, credentials you control, failover, cost controls, observability. The boring infrastructure that keeps a system alive after launch.
Led by Matías Baglieri and Carolina Fogliato, we focus on one thing:
AI leadership that builds. Not just advises.
Ask us whether your finance team could defend last quarter's AI forecasts under audit.
We'll tell you what the manifest would have captured. See model lineage for the record.
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