Agent actions
Capture every trace, event, log, and metric your agents emit — a complete, structured record of what your fleet actually does in production.
Platform
Behaviour runtime intelligence for AI agent fleets
PUVINoise™ observes agent behaviour, understands intent, predicts outcomes, and recovers automatically — across a multi-tenant control plane built for production.
Live
Behaviour signals from instrumented fleets
Governed
Policy-aware autonomous recovery
Scoped
Multi-tenant observation boundaries
MTTR
Recovery intelligence leadership can track
How it works
Four layers, one control plane
PUVINoise turns raw agent activity into governed, autonomous outcomes — each layer building on the one before it.
Behaviour signals
Sessions, decisions, tool calls, and state changes become high-fidelity behaviour signals you can reason about — not scattered stderr.
Behaviour intelligence
Correlate and detect across the whole ecosystem. Surface drift, anomalies, and policy gaps, and predict outcomes before they become Runtime Cases.
Autonomous outcomes
Governed policies and recovery close the loop — remediating issues automatically with full audit trails and human overrides.
Command Centre
Operational situation, runtime controls, and execution context for agent fleets.
The Command Centre answers the operator's core questions: what is running, what changed, and what requires intervention. Situation views aggregate fleet state without ad hoc dashboards, and runtime controls respect execution context — who triggered an action, under which policy, in which tenant.
Shared situational picture across teams and tenants
Controls aligned to execution context, not orphaned scripts
Faster handoffs between engineering, SRE, and agent ops
Behaviour intelligence
Detect drift, anomalies, and policy gaps on governed behaviour surfaces.
Agents fail quietly — drift in tool use, gradual policy erosion, anomalous sequences that classic uptime metrics miss. Behaviour intelligence consumes telemetry and behaviour signals from instrumented agents to highlight what diverged from expected patterns, in language security, agent ops, and engineering all share.
Earlier detection before customer impact
Shared language across security, agent ops, and engineering
Signal quality rooted in SDK instrumentation
Runtime Case management & recovery
MTTR-minded workflows and recovery lifecycle visibility for agent Runtime Cases.
Agent Runtime Cases are how production agent failures are tracked and recovered. PUVINoise connects detection, triage, mitigation, and post-case learning — with recovery intelligence that helps leaders reason about MTTR and lifecycle stage, not vanity counts.
Clear Runtime Case lifecycle for autonomous workflows
Recovery metrics leadership can track over time
Correlation back to behaviour signals and Command Centre context
Autonomous outcomes
Governed autonomy, not blind automation
Every automatic action passes through policy, with audit trails and human overrides — so recovery is trustworthy at fleet scale.
Policy engine
Define what agents may do and how the platform may respond. Guardrails are explicit, versioned, and reviewable.
Autonomous recovery
Predicted anomalies trigger governed remediation — retries, rollbacks, or containment — before they reach production impact.
Recovery intelligence
Track MTTR, lifecycle stage, and recovery success across the fleet, with correlation back to originating behaviour signals.
Architecture
Architecture & multi-tenancy
Multi-tenancy is not a sidebar feature — it is how enterprises onboard teams without shared blast radius. PUVINoise describes control plane boundaries, data paths, and what reviewers should validate during security assessment.
Tenant boundary
SDK
Ingest
Control Plane
Command Centre
Behaviour Intelligence
Runtime Case Management
Recovery
Legend: — tenant boundary · → data flow
Proof
Case studies, benchmarks, and trust
Buyer-trust surfaces linked from the product journey — validate fit before commercial close.
Case studies
Reference scenarios from SDK emit to governed recovery — no invented metrics.
Case studies →Benchmarks
Five-dimension evaluation rubric to score on your fleet.
Benchmarks →Trust Center
Security, Privacy, OpenTelemetry, Roadmap, and Documentation.
Trust Center →Works across industries
One runtime spine. Different blast radius.
Healthcare, fintech, edtech, B2B SaaS, enterprise B2B, and operations share the same layers — observe, understand, govern, recover — with industry-shaped risk language. Dedicated hubs live under Solutions.
Healthcare
Audit trails, consent-aware tool use, and MTTR when clinical or ops agents drift.
Healthcare solutions →Fintech
Policy evidence and governed recovery when payment-adjacent agents fail in production.
Fintech solutions →EdTech
Multi-org tenancy and safe behaviour signals when learners and staff are in the path.
EdTech solutions →B2B SaaS
Per-customer agent fleets on a shared control plane — isolation without operational silos.
B2B SaaS solutions →Enterprise B2B
Cross-team agents with one situation story from signal to recovery.
Enterprise B2B solutions →Operations
Shared-service agents with Runtime Case discipline and recovery intelligence leadership can track.
Operations solutions →Answers
What decision-makers ask first
Short, factual answers for teams evaluating behaviour runtime intelligence — written for humans and readable by assistants.
What is PUVINoise?
PUVINoise is a behaviour runtime intelligence platform for AI agent fleets. It observes live agent behaviour, correlates signals into operational context, and supports governed recovery across a multi-tenant control plane.
Why does runtime governance matter for MTTR?
Agent failures appear while agents are running — tool errors, policy skips, and cascading retries. Runtime signal, policy, and recovery on the same path shorten time-to-detect, time-to-decide, and time-to-recover.
Does PUVINoise replace my agent framework or model provider?
No. PUVINoise attaches at runtime and is framework- and provider-agnostic. You keep your frameworks, models, and hosts; the control plane governs behaviour without a stack migration.
Who is PUVINoise for?
Teams that run AI agents in production — across healthcare, fintech, edtech, B2B SaaS, and operations — and need multi-tenant observation, behaviour intelligence, Runtime Case workflows, and recovery metrics leadership can track.
Do you build separate products per industry?
No. Industry pages are lenses on the same platform: observability, governance, multi-tenant control plane, and recovery. Risk language changes; the runtime spine does not.
Where can I see Pricing and AI credits?
Platform Pricing and AI credits are published on the Pricing page. Engineering engagements are scoped separately — start from Pricing for product plans, or Contact for an Engineering Consultation. Use Benchmarks to score fit during evaluation.
See the platform on your fleet topology
Walk through Command Centre, behaviour intelligence, and Runtime Case workflows with our team — or review Pricing and Benchmarks first.