Know where agentsfail before launch

For legal, finance, and accounting AI teams — finding the failures your eval pipeline doesn't catch.

Assess a workflowSee a sample scorecard
Expert-gradedAttorneys, CPAs, analysts
One agentFull failure surface
Failure taxonomyCategorized by severity

Evaluators from Goldman Sachs · McKinsey · Deloitte · AmLaw 100 firms

Sample scorecard
42-case benchmark
4 blocked9 review-required11 long-tail
Contract review — change of controlCase 23 of 42
Agent output

Section 8.2(b) permits assignment with prior written consent of the board.

“No change-of-control restriction identified.”

Deemed-assignment provision missedCRITICALCross-reference dependency

Section 12.4 deems any change in beneficial ownership above 50 % an assignment, triggering counterparty consent and termination rights. The agent treated 8.2(b) as the sole assignment provision.

Agent trace
Retrieval — pulled §8.2(b) assignment clause
Reasoning — interpreted consent requirement
Cross-reference traversal — missed §12.4 deemed-assignment triggerFAILED
Expert review
Senior M&A attorneyCONFIRMED
Senior M&A attorneyCONFIRMED
Recommended action

Flag Section 12.4 deemed-assignment trigger. Obtain counterparty consent or restructure pre-closing.

Launch guidanceBLOCKED

Do not ship — counterparty consent required under Section 12.4 before closing

{ XR-REF-003·cross-reference_traversal_—_missed_§12.4_deemed-assignment_trigger·blocked }
{ }

Every verdict exports as structured JSON — for CI/CD gating, regression tracking, and remediation routing.

Why this catches what you miss

Tests the agent, not just the model.

Yours

Eval prompts test what the model knows in isolation.

Ours

We test what your agent does end-to-end — retrieval, reasoning, cross-references — in the workflow context where failures actually happen.

Expert-graded, not spot-checked.

Yours

Ad-hoc review by generalists or internal rubrics you wrote.

Ours

Every case graded by domain experts who’ve seen these failures in practice — not from a prompt.

Structured verdicts, not review notes.

Yours

Unstructured feedback in a doc.

Ours

Every failure gets a code, severity tier, root cause trace, and remediation target. Exports as JSON for CI/CD gating.

Who it's for

AI products shipping to domain experts

Legal AI

Jurisdiction-dependent failures that change enforceability.

Contract reviewDiligenceClause interpretationPlaybook enforcement

Finance AI

Regulatory gaps that change credit decisions.

Credit reviewCovenant analysisDeal memo supportComps research

Accounting AI

Classification errors that change financial statements.

Close workflowsReconciliationException handlingClassification logic
How it works

One workflow to launch decision.

1
1–2 daysFree

Connect your agent

Point us at an endpoint, share transcripts, or give us staging access — any model, any harness. We design the benchmark around your workflow.

2
1–2 weeksFree

First benchmark

Domain experts grade 35–50 cases end-to-end. You get a scorecard, root cause traces, and a ship-or-fix recommendation.

3
Ongoing

Every deploy, re-benchmarked

When the model or workflow changes, the benchmark re-runs. New edge cases fold in each cycle. Structured JSON for CI/CD gating.

One workflow. One scorecard.
A clear recommendation.

Most teams discover their worst failure modes after an enterprise customer does.

Assess a workflowor email team@omaratechnologies.com

Omara was built to solve a problem we kept seeing: AI teams shipping into expert workflows without expert-grade evaluation.

— Rudradev Roy, founder