The immune system for AI agents
Detect, score, and repair trust breakdowns across your AI workflows in real time. From silent failures to visible recovery loops.
No setup required • See real examples in seconds
Live trust funnel, stage loss, and batch intervention outcomes across your AI system.
See which interventions actually improved trust, and which did not.
Built for teams running real AI systems
Designed for teams who can't afford silent AI failures
- •Agent workflows
- •Multi-step pipelines
- •Internal AI tooling
Why teams use Recon.AI
- Detect silent failures before users do
- Measure trust across every AI task
- Validate recovery with real outcomes
- •Blind retries
- •Guessing if outputs are correct
- •No visibility into failures
- •Measurable trust scores
- •Visible recovery loops
- •Operator-level control
A full trust loop, not just monitoring
Most AI systems do not fail loudly. They drift, hallucinate, degrade, or produce outputs that look right but are not. Recon.AI makes those failures visible and fixable.
Detect
Identify where outputs drift, degrade, or fail expectations before the damage compounds.
Score
Assign a Reflex Score to each task and output so trust becomes measurable, not assumed.
Repair
Trigger retries, reprompts, and recovery workflows when the system detects weak behavior.
Validate
Confirm outcomes, preserve attribution, and prove whether interventions actually improved results.
Learn
Track patterns across missions, tasks, and batch runs so trust improves over time.
Most AI systems fail quietly. Recon.AI makes every failure visible—and fixable.
From system overview to exact replay
Track trust at the system level, then drill into the exact mission, task, or batch run that needs attention.
Mission Detail
See how entire workflows perform. Identify weak paths, low acceptance rates, and where trust breaks across a mission.
Find where trust breaks at scale
Task Trust Replay
Replay a task from generation to outcome. See scoring changes, recovery attempts, and exactly what improved.
Understand what actually happened
Batch Run Detail
Evaluate intervention impact across multiple targets. See which tasks recovered, failed, or still need attention.
See what actually improved trust
No setup required • See real examples in seconds
Start with system health, drill into missions, replay tasks, and validate interventions.
From black box to full replay
Every task becomes a replayable timeline: generation steps, scoring changes, recovery attempts, and final outcome. No guessing. No blind spots.
Replay what happened from generation to recovery to final outcome.
Your TrustOps command center
Operate trust like a system. See where behavior breaks, what got repaired, and whether the intervention actually worked.
Conversion Dashboard
See trust movement across the system, spot drop-off points, and monitor recovery performance.
Mission Detail
Drill into weak workflows, compare outcomes, and identify where trust leaks inside a mission.
Task Trust Replay
Replay the lifecycle of a task step by step, from generation to scoring, recovery, and final outcome.
Batch Run Detail
Measure intervention impact, compare before-and-after signals, and inspect which targets recovered or failed.
Don't just detect failures. Fix them.
Recon.AI does not stop at observation. It retries intelligently, reprompts strategically, validates outcomes, and measures improvement over time.
Turn AI behavior into measurable signals
If you cannot measure trust, you cannot improve it. Recon.AI turns silent behavior into visible operational signals.
A new layer for AI systems
DevOps manages infrastructure.
MLOps manages models.
TrustOps manages behavior.
Works across your AI stack
Recon.AI fits into agent workflows, API-based pipelines, multi-step systems, and internal operator loops where trust needs to be measurable.
Stop guessing. See what your AI is actually doing.
Recon.AI helps teams move from silent failures to visible recovery loops, measurable trust signals, and operator-grade control over AI behavior.
No setup required • See real examples in seconds