# 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.

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## 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

1. **Monitor.** Run representative and noisy data through your agent or model to establish expected ranges for accuracy, repeatability, escalation rate, cost, and latency.
2. **Evaluate.** Swept AI evaluates behavior in development, staging, and production, tracking drift, outliers, and regressions.
3. **Control.** When behavior violates a policy or falls outside the baseline, Swept blocks actions, routes to approval, or triggers fallback flows.

Integrates 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.

[Contact us](/contact)