Nautilus Studio now supports side-by-side regression replay at scale.

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NAUTILUS STUDIO

Your AI delivery cockpit.

Visualize prompt chains, tool calls, retrieval context, and model decisions in one interface built for engineering teams.

WORKSPACE

From prototype to production without switching tools.

Prompt Canvas

Compose prompt nodes with explicit I/O contracts and test all branches against real or synthetic datasets.

Trace Replay

Replay any request deterministically, inspect token-by-token output, and compare behavior before and after code changes.

Eval Benchmarks

Track quality gates for correctness, policy compliance, and response consistency across model and prompt updates.

Release Gates

Block deployments until required metrics pass thresholds configured by your platform and product teams.

TEAM FLOWS

Built for real engineering collaboration.

  • Branch Reviews: review prompts and configs in pull requests.
  • Session Notes: annotate traces to preserve debugging context.
  • Role Permissions: separate authoring, approval, and release rights.
  • Approval Trails: cryptographically signed deployment approvals.
  • Incident Replay: reproduce historical request paths from stored traces.

STUDIO MODES

Choose the right mode for each stage.

  1. Sandbox Fast local experiments with low-friction defaults.
  2. Staging Production-like traffic simulation and regression checks.
  3. Controlled Rollout Canary releases with automated quality and latency guardrails.
  4. Full Production Live dashboards, incident hooks, and compliance exports.

STUDIO COMPONENTS

One interface, specialized workspaces.

Workspace Primary Purpose Key Output
Canvas Design prompt and tool flow graph Versioned chain configuration
Evaluate Run quality and policy benchmark suites Release-ready scorecard
Observe Inspect live traffic and response lineage Operational timeline with alerts
Ship Promote builds with approvals and staged rollout Signed deployment artifact

NEXT STEP

Turn experiments into reliable product features.

Build in Studio, validate with evals, and launch confidently with traceable releases.