Playground

The essential building blocks for AI agents.

Model entities, relationships, and structured context — Palantir-grade.

Real-time event processing — from passive to proactive.

Extend how your agent thinks.

Gotham-style decision intelligence.

Military-grade scenario modeling.

Workflows, retries, budgets, concurrency.

External tool capabilities.

Scale with queues, scheduling, fault tolerance.

React components for AI agents.

Multi-user agents and shared sessions.

Location intelligence for defense/logistics.

Trace, log, and replay.

Production guardrails.

Enterprise and defense-grade security.

Benchmark and detect regressions.

Route, fallback, optimize.

Intelligence-grade knowledge systems.

Persistent agent memory.

Templates, debugging, simulation.

Self-driving agents: continuous operation, goals, and self-reconfiguration.

Systems that improve from experience without manual intervention.

Knowledge that updates, self-corrects, and evolves over time.

Test without breaking production: A/B, shadow, canary.

Every decision explained — required for defense and enterprise.

Threat modeling, adversarial simulation, red-team — Sherpa-grade.

Multiple autonomous systems cooperating with trust boundaries.

Domain-specific models for defense, fintech, healthcare, logistics.

Avoid groupthink: diverse reasoning, contrarian agents, consensus.

Decide HOW to execute: cost, latency, resources, caching.

Who controls the system: objective alignment, global policies, constraints.

Internal world representation, prediction, and uncertainty quantification.

Balance cost, risk, time, impact — Pareto-optimal decisions.

Systems that evolve HOW they think, not just what they answer.

Close the loop: world → system → decision → action → world.

Hybrid reasoning: symbolic + probabilistic + neural.

Agents as collective mind: consensus, debate, swarm.

Ethical boundaries, doctrine, and mission-level objectives.

System knows its capabilities, limits, and blind spots.

Prove system properties. What almost nobody does.

Decision coverage, not code coverage. Know where the system fails.

Understand the system as an organism: profiles, drift, emergence.

Mission control, kill switches, mode switching — production-grade ops.

Human ↔ system integration: intent, controls, trust, approval.

Multiple Sherpa systems cooperating with federated intelligence.

Simulate countries, markets, conflicts — strategic-level modeling.