Self-correcting agents for the future of work
We design, evaluate, and deploy deep research and planning systems that learn from feedback, recover from failure, and systematically prepare your next project.
Evidence base built from docs, code, and the web so every claim is verified and auditable.
- Citations and provenance tracking
- Structured design taxonomy
- Continuous source updates
Monte carlo search over strategies to produce delivery scaffolds and robust cost/timeline estimates.
- Deterministic sampling of strategy rollouts
- Scaffolds: interfaces, milestones, tests
- Sensitivity analysis and risk surfaces
Resilient planning agents
Evidence grounded rollouts that de-risk scope, cost, and delivery.
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01
Ground
Collect docs, code, data and constraints. Build a verifiable research base with citations.
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02
Plan
Search strategies using rollouts and sampling; compare plans against goals and risks.
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03
Scaffold
Generate detailed project scaffolds: interfaces, milestones, acceptance tests, and owners.
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04
Validate
Backtest projections, run evals, and stress test assumptions. Iterate until robust.
Research-driven agent that produces evidence-backed briefs, task lists, and risk surfaces for real world projects.
Generates production-ready scaffolds - service and data designs, boundaries, schemas, and interfaces.
Monte Carlo projections for scope, cost, and timeline. Sensitivity analysis via probabilistic sampling and scenario rollouts.
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Tell us about your workflow and what success looks like.