AI agents that get better with every release.
BehaviorStudio captures behavioral signals, attributes failures to specific skills, and gates every release against regressions. Built for regulated industries where behavioral drift isn't a bug — it's a liability.
The Problem
Agent quality fails silently.
The architecture to fix it doesn't exist in your stack.
01
Feedback loses context.
A signal flagged in Slack is context-dead before it reaches the team that can act on it. The conversation, the prompt state — gone.
02
Edits cause invisible conflicts.
Fix one behavior, break another. Without a model isolating changes by tenant, market, locale, and cycle, every fix is a gamble.
03
Eval suites don't grow.
Your test suite was frozen at launch. Every new failure is a surprise — because no one built coverage for what came after.
How It Works
The Calibration Cycle
A four-stage pipeline that compounds agent quality with every release.
Stage 01
Observe
Turn-level annotation, async capture, and voice-triggered evaluation — all feeding a unified observation schema built for downstream attribution.
Stage 02
Attribute
The Foundry Attribution Engine maps every signal to its root skill. The Contradiction Engine flags conflicts across all five scope dimensions before anything ships.
Stage 03
Validate
Impact prediction models forecast behavioral effects before deployment. The Regression Gate enforces zero regressions as an architectural constraint — not a goal.
Stage 04
Ship
Every edit scoped, validated, and auditable across tenants, markets, locales, and release cycles. Built for environments where behavior has legal consequences.
System architecture
Capabilities
Nine capabilities. Three engines. One integrated architecture.
The engines are integrated. The Observation Engine feeds Attribution, which feeds Validation. This chain is the product.
Observation Engine
Turn-level Annotation
Every agent response annotatable with behavioral feedback. Prompt state, model output, and conversation history captured together — at the moment of observation.
Voice Eval Trigger
Trigger evaluations by voice during live sessions. Designed for clinical and pharma environments where breaking conversation flow isn't an option.
Async Observation Capture
Capture observations from logs, replays, or user reports. Every signal receives the same structured context schema — regardless of when it was captured.
Attribution Engine
powered by Foundry Agent orchestration
X-Ray Mode
Full pipeline visibility into how behavioral decisions propagate. See exactly which prompt, tool call, and decision path produced any output.
Skill Attribution
Every behavioral outcome attributed to a specific agent skill. Know which capability owns the fix before writing a line of code.
Contradiction Engine
Detects conflicts between a proposed edit and existing behavioral standards across all five scope dimensions — before the change is applied.
Validation Engine
Impact Prediction
Forecast the downstream behavioral effect of every proposed change. See affected conversations and severity shifts before committing.
Regression Gate
Blocks any deployment that would alter a validated behavior. An architectural constraint — not a manual review step. Every fix stays fixed.
Auto-Generated Evals
Every resolved observation becomes an eval case. Test coverage compounds with every Calibration Cycle — no manual authorship required.
The Architecture
20 years of conversational AI architecture, compressed into one platform.
Not a monitoring dashboard with extra features. A behavioral calibration architecture — three proprietary innovations, deeply integrated, built for regulated environments.
The 5-Dimensional Scope Model
Isolates behavioral edits across tenant, product, market, locale, and release cycle. Makes surgical, non-breaking changes possible across multi-market deployments. The model emerged from two decades of watching one-context fixes silently break another.
The Contradiction Engine
Identifies conflicts between proposed edits and existing behavioral standards before changes are applied — across all five scope dimensions simultaneously. Regression tests tell you what broke. The Contradiction Engine tells you what would break.
The Calibration Cycle Model
Replaces ad-hoc patching with structured, time-boxed quality loops. Each cycle compounds: observations become attributions, become validations, become evaluations. The system gets more accurate every cycle — not just larger.
These three innovations are inseparable. The scope model informs the Contradiction Engine, which informs the Regression Gate, which informs every auto-generated eval. This integration is the product. It cannot be replicated by assembling individual tools. It can be licensed.
Use Cases
Any agent where behavioral quality has consequences.
Pharmaceutical
The 5-Dimensional Scope Model isolates behavioral edits by market and locale. A correction for one jurisdiction doesn't create off-label exposure in another.
Financial Services
Behavioral drift in a regulated customer-facing agent isn't a software bug — it's a regulatory finding. The Calibration Cycle produces the audit trail.
Legal
The Contradiction Engine prevents a behavioral edit in one practice area from conflicting with another. Every change traceable. Every hallucination caught before client delivery.
Clinical
Voice Eval Trigger enables real-time behavioral flagging in live clinical sessions — without interrupting care workflows. Turn-level quality at a scale manual review can't match.
Insurance
The Regression Gate ensures behavioral changes validated for compliance stay validated. No regressions. No surprise audit findings.
Enterprise
Multi-tenant, multi-market deployments face a combinatorial scope problem. The 5-Dimensional Scope Model was built for exactly this environment.
The Shift
Calibration cycles, not sprint reports.
Properties of the architecture. Not targets.
<20 min
Observation to fix
Automated attribution eliminates forensic work. The system identifies the failure, the owning skill, and the downstream impact — before a human decides anything.
0
Regressions per release cycle
Not a target. An architectural constraint. The Regression Gate blocks any deployment that would alter a validated behavior. No exceptions.
+25%
Eval coverage per cycle
Every resolved observation becomes an eval case. After four cycles, coverage is roughly double the starting baseline. Compounding, not linear.
100%
Edit traceability
Every behavioral change scoped, attributed, validated, and logged from observation through deployment. The architecture makes undocumented changes impossible.
Early Access
Behavioral quality doesn't fix itself.
Early access is open to teams building AI agents in regulated environments — and to consulting and systems integrator practices exploring behavioral calibration as a licensable infrastructure layer.
You're on the list.
We review every submission personally — expect a response within 48 hours.