Agent Quality & Integrity · Stealth · 2026
CirceAI continuously validates, scores, and certifies autonomous AI agents before and after they reach production — bringing database-grade integrity principles to probabilistic systems.
Validate · Score · Certify
AI agents are probabilistic by nature — they mutate behavior across runs, interact with tools unpredictably, and drift over time. Yet there is no systematic quality gate before they reach production. The gap isn't observability. It's integrity.
of enterprise AI deployments report unexpected agent behavior within the first 90 days of production.
average cost of an AI-driven compliance failure in regulated industries — before litigation and reputational damage.
existing platforms define agent readiness for autonomous deployment — only performance in isolated tests.
EU AI Act and emerging US and UK regulation require documented evidence of agent reliability before deployment in high-risk categories.
Our founders come from enterprise database systems at Oracle. Databases don't trust queries blindly — they enforce constraints, transactions, and integrity checks to guarantee consistency. AI agents today have none of this. We are building that layer.
"We don't eliminate uncertainty in AI agents. We make it measurable, testable, and governable."
Explicit rules that queries cannot violate, enforced at the system level before execution.
Agent behavior is only observed after the fact, with no pre-execution constraint layer.
Data consistency validated continuously across operations, transactions, and state changes.
Behavior mutates unpredictably across model updates, prompt changes, and tool interactions.
Complete, deterministic logs of every operation with rollback and replay capability.
Observability tools capture what happened but cannot explain why or prevent recurrence.
Schema migrations and updates pass through structured validation gates before production.
Agents go directly from development to production with no certification of readiness.
CirceAI sits before and around deployment — not just inside it. Three phases, one outcome: confidence that your agent is ready to operate without supervision.
Behavioral test suites covering tool usage, decision workflows, and edge-case scenarios. Regression detection across model and prompt changes. Deterministic scoring of probabilistic outputs.
Unit tests for agentsSynthetic and real-world replay testing in staging. Drift detection as models update. Confidence scoring per capability, not just per response. Grounding verification against enterprise data.
Post-build · Pre-prodA structured go/no-go decision based on integrity scores, policy compliance, and autonomy confidence thresholds — not human intuition. Documented evidence for regulatory requirements.
CertificationOngoing behavioral monitoring with constraint enforcement and anomaly alerting. Automatic rollback triggers when drift exceeds thresholds. Continuous improvement loop back to test suites.
Always-onInstead of raw accuracy rates and hallucination percentages, CirceAI produces system-level scores that answer the only question that matters: can this agent safely run without human supervision?
A composite measure of whether an agent is ready to operate without human-in-the-loop intervention across its defined task scope.
Behavioral consistency across repeated runs of the same task under varying conditions, model versions, and data states.
How faithfully agent outputs adhere to enterprise data, policies, and constraints — rather than model priors or hallucination.
Accuracy and safety of external tool invocations: API calls, database writes, and system integrations made by the agent.
The existing landscape addresses fragments of the problem — observability, evals, safety, debugging. CirceAI occupies the missing position: system-level certification of agent readiness for autonomous deployment.
| Company | Category | What they answer | What they miss | CirceAI answers |
|---|---|---|---|---|
| Arize | Observability | What did your agent do in production? | Does not define readiness to deploy | Is this agent safe and reliable enough to deploy in the first place? |
| Braintrust | Eval CI/CD | Did this prompt or model perform well in tests? | Task-level evals, not system integrity | Does the entire agent system behave reliably under autonomy? |
| Maxim | Simulation | How might the agent behave in these scenarios? | No rigorous integrity scoring or release gate | Is it certified for autonomous production deployment? |
| Patronus | Safety | Is this agent response unsafe or hallucinated? | Safety ≠ operational reliability | Is it reliable enough to run autonomously, not just safe enough to not flag? |
| LangSmith | Debugging | Why did this agent fail inside LangChain? | Ecosystem-locked, not a cross-framework system of record | A framework-agnostic quality and integrity record for every agent. |
We are going deep in two verticals before expanding. Both are defined by high-stakes autonomous decisions, tight regulatory accountability, and the strongest business case for a quality gate.
Agents autonomously route shipments, negotiate vendor contracts, and manage inventory at scale. A single miscalibrated agent can cascade across thousands of supply nodes before any human notices. Continuous integrity scoring catches drift before it propagates.
Procurement · Logistics · Vendor opsTrading agents, fraud detection pipelines, and credit decisioning systems operate at machine speed with regulatory-grade accountability requirements. Circe provides the documented certification trail that compliance teams and regulators require.
Risk · Compliance · Trading · Lending"She transformed those who came unprepared — but Odysseus, forewarned and grounded, walked through her island as master."Homer, The Odyssey · The founding principle of CirceAI
CirceAI is in stealth. We are engaging enterprise design partners in supply chain and financial services, and investors who understand the patience category creation requires.
We are looking for teams deploying agents in supply chain or financial services who want to co-develop the quality gate for their stack. Early partners shape the product and the category.
team@circeai.netWe are raising a pre-seed round from investors who recognize that agent quality and integrity is infrastructure — not a feature — for the autonomous enterprise.
investors@circeai.net