Backed by
Y Combinator
Why agents stall in pilots
Agents don’t fail the demo. They fail the close.
Most teams check agents three ways: basic deterministic rules, an LLM judge, and humans sampling the rest. The gap is the middle: judge models miss what the agent missed, rules only cover what someone wrote down, and everything else lands on people. That’s why autonomy stays low and pilots never graduate.
Definite gates the action on the evidence behind it.
Example
Invoice posted
Priced against last year’s rate table. Matched the PO anyway.
Example
Reconciliation match
Two statements disagreed. The agent picked one silently.
Example
Fee accepted
A surcharge that was never in the contract, paid without question.
Example
Refund issued
No order or shipping evidence ever retrieved.
Definite doesn’t just ask, “Can the agent do this?”
It recomputes what the output should be and blocks anything that doesn’t match.
Two ways to start
Start with an audit. Keep the engine.
You don’t have to trust us. The first engagement proves the money. Then the same engine runs under your agents in production.
Trace-to-Gate
Find the errors your agents already made.
Send us historical agent traces and logs from any builder in any format, or last quarter’s statements. Definite re-verifies every decision retroactively and returns a discrepancy report: what was wrong, what it cost, with the evidence attached.
Re-verify past agent decisions against source documents
Recompute fees and charges against contracts and rate tables
Flag stale, conflicting, or unsupported evidence
Every finding ships with receipts, not opinions
Runtime Verification Engine
Verify every action before it lands.
The engine sits at the action boundary. Every output is blocked by default and verified: numbers are recomputed from source data, everything else is checked against the evidence. Then it is cleared, returned to the agent to fix, or escalated. Either way, a signed, replayable evidence record is kept.
Default-blocked: nothing reaches production unverified
Failed checks return to the agent like compiler errors, and most fix themselves in seconds
Gates learn: recurring failures harden into permanent checks
Signed, replayable records for every decision
Evidence-aware verification
Definite checks the action, the math, and the facts behind it.
A normal permission check asks whether the agent can access a tool. Definite goes further. It checks whether this specific action is justified by the evidence the agent used.
Block
Missing evidence
The agent wants to act, but required source data was never retrieved.
Example: An invoice posts without the delivery receipt ever being pulled.
Review
Stale evidence
The agent relies on an old document, memory, or profile field that may no longer be valid.
Example: Charges priced against a superseded rate table.
Review
Conflicting evidence
Two sources disagree and the agent tries to proceed silently.
Example: The processor statement and the ledger disagree, and the agent proceeds silently.
Block
Unauthorized evidence
The agent uses a source that should not justify this action.
Example: A note from a chat thread is used to justify a payment change.
Deterministic policy engine
Gates that learn like a compiler’s error list grows.
Gates come from your own history: traces, logs, and past failures.
And they keep improving: when the same class of failure recurs, the correction is compiled into a new or tighter gate, so the system hardens with volume instead of drifting.
The model does the work. It never grades its own answer.
Ingest
Historical traces and logs become the initial gate set. Each gate is annotated with the failures it would have caught.
Verify
Every action runs the gates at runtime. Same action, same evidence, same decision, every time.
Harden
Failures feed back automatically. Your team can review and veto any gate change, but the loop doesn’t wait on anyone.
How Definite works
Every posting, payment, and match is verified before it executes.
Definite sits between the agent and the systems it writes to.
The default state of every action is blocked. Nothing reaches production unverified.
1
Agent proposes an action
Post to the ERP, match an invoice, issue a payment, resolve an exception.
2
Definite assembles the evidence
Contracts, rate documents, POs, receipts, and ledger records, all checked for freshness and conflicts before they’re used.
3
The engine verifies
Numbers are recomputed from the sources and compared to what the agent produced. Everything else is checked against the assembled evidence.
4
Clear, return, or escalate
Cleared actions proceed instantly. Failures go back to the agent with the reason, like a compiler error, and most resolve in seconds without a human. Only genuinely conflicting evidence escalates.
5
The decision is recorded
A signed, replayable record: the action, the evidence, each check’s result, and why. Anyone can audit any decision without trusting us or the agent.
Measured, not promised
Verification beats a bigger model.
On a published reconciliation benchmark, Definite’s verification loop took the cheapest model in the paper’s test panel past GPT-5, the paper’s best performer, on every metric at roughly 1/40th the cost per record, with zero false alarms. A new best score on the benchmark.
Simple integration
Add Definite at the action boundary.
You do not need to rebuild your agent stack. Add Definite before the tools that matter most.
Start with one workflow, like invoice posting, reconciliation, or fee audit. Expand as agents earn more autonomy.
Before
UNGATED PATH
Direct tool access. No evidence, policy, or audit check before execution.
Agent
→
Tool
→
System
No policy checkpoint
No evidence
No signed audit
After
DEFINITE GATED
Definite checks evidence, policy, and signing before the tool runs.
Agent
→
Gate
→
Tool
Evidence
Policy
Signed audit
Allow
Review
Deny
