Ship AI features faster with real-time supervision and guardrails
Swept AI gives development teams the visibility, control, and guardrails needed to build reliable AI agents and features without slowing down releases. Catch drift, flag regressions, and enforce policies automatically across environments.
Trusted by engineering and platform teams building high-impact AI products across regulated and operationally-critical industries.
Why development teams struggle with AI in production
Unpredictable behavior in real-world traffic
Golden-path prompts and synthetic datasets don't reflect the messy, long-tail inputs real users generate.
Difficult debugging and reproducibility
LLM behavior changes with model updates, temperature adjustments, context shifts, or data updates, often without clear signals.
Manual QA doesn't scale
Reviewing transcripts, spot-checking outputs, and fire-drilling incidents consumes engineering time that should be spent building.
Swept AI equips development teams with the tools to build, ship, and maintain AI systems with predictable behavior across environments.
Supervision for developers building real-world AI products
Catch regressions fast
Automatically detect when behavior deviates from baselines as models, prompts, or data change.
Shorten time-to-debug
Replay bundles include inputs, plan traces, tool calls, versions, and recent changes so developers can reproduce issues instantly.
Prevent bad outputs in production
Policies block unsafe or incorrect responses before they reach users or downstream systems.
Ship with confidence
Clear baselines and measurable improvements replace guesswork, saving dev teams hours of manual testing.
How Swept AI Works
Monitor
Run representative and noisy data through your agent or model to establish expected ranges for accuracy, repeatability, escalation rate, cost, and latency.
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Evaluate
Swept AI evaluates behavior in development, staging, and production; tracking drift, outliers, and regressions.
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Control
When behavior violates a policy or falls outside the baseline, Swept blocks actions, routes to approval, or triggers fallback flows.
Learn moreIntegrates via API, SDK, gateway, or agent framework. No model retraining required.
What development teams are using Swept AI for
Detect regressions before release
Catch prompt changes, model updates, or integration changes that introduce unexpected behavior.
Improve agent reliability
Track tool-use patterns, sequence stability, escalation behavior, refusal rates, and extraction quality.
Debug faster with replayable bundles
Get a single package with everything needed to reproduce a failure locally or in staging.
Protect production systems
Block high-risk actions, enforce business rules, and prevent cascading failures from agent drift.
Measure improvements over time
Quantify repeatability, stability, and accuracy to show progress and justify launches.
Integrates with your stack, aligned with your security posture
Compatible with any LLM, vector DB, or agent framework
Works with gateways, orchestrators, and workflow engines
Zero data retention options
PII masking/redaction
VPC or on-prem deployment
No model training or fine-tuning required
CI/CD friendly
Built for developers building AI systems
Build and Test
- API/SDK for easy integration
- Local and staging baselines
- Scenario testing with noisy inputs
- Drift and regression detection
- Behavior scoring and evaluation suites
Deploy and Operate
- Real-time policy enforcement
- Replayable incident bundles
- Version tracking for prompts, models, and tools
- Role-based approval gates
- Dashboards for stability, cost, and latency
Move from AI promise to proof.
Run a free evaluation, supervise in production, and share proof with reviewers.
Talk to our team