Automate the Work That Should Not Require a Human Every Time
We engineer reliable agentic execution engines, type-safe tool interfaces, and production RAG pipelines designed with the rigor of traditional systems engineering.
AI prototypes that demo well routinely fail in production. The gap between demo and reliability is an engineering problem — and it requires engineering discipline to close.
State Machine with Schema Validation & Circuit Breakers
AI prototypes that demo well but fail reliably in production
Many businesses attempt to implement AI automation using basic prompt wrappers or open-ended agent frameworks, only to experience hallucinations, schema corruption, runaway API billing, and lack of accountability when things go wrong.
Typical Symptoms We Diagnose
- Unconstrained while loops burning API credits without completing the intended task
- Malformed JSON tool parameters crashing downstream database queries or APIs
- Zero audit trail or observability into why a model made a specific automated decision
- Fear of destructive automated actions without human approval gates
Engineering Outcomes
Deterministic Convergence
State-machine driven agent loops with bounded steps and structured error-recovery prompts.
Granular Token Governance
Hard per-task spending ceilings and circuit breakers preventing runaway API loop billing.
Human-in-the-Loop Oversight
Cryptographically signed approval hooks for high-risk financial, data, or external API actions.
What We Own & Deliver
End-to-end technical responsibility, not partial hand-offs.
Deterministic Agent Loop Engineering
Constructing resilient multi-step reasoning engines that break complex workflows into discrete, check-pointed state transitions.
Concrete Deliverables
Type-Safe Tool Interfaces & Sandboxing
Wrapping external APIs, databases, and filesystem tools in strict runtime schema validators (Zod) with automated self-correction.
Concrete Deliverables
Enterprise RAG & Knowledge Retrieval
Building high-precision semantic search and hybrid keyword retrieval pipelines with deterministic source citations.
Concrete Deliverables
Observability & Token Telemetry
Implementing full OpenTelemetry trace recording for prompt tokens, completion tokens, latency, and step decision trees.
Concrete Deliverables
How The Engagement Runs
Disciplined async execution designed to minimize meetings and sustain high engineering velocity.
Workflow Decomposition
Map human workflows into discrete, verifiable decision trees with clear inputs and failure boundaries.
Schema & Tool Contracts
Build type-safe tool execution interfaces and mock test harnesses to assert model parameter compliance.
Loop Engine & Checkpoints
Implement finite-state execution loops with append-only state persistence in SQLite/D1.
Guardrails & Rollout
Add step limits, token budget circuit breakers, human approval triggers, and full trace telemetry.
Frequently Asked Questions
Do you build generic AI wrappers or custom systems?
We design custom, production-grade agentic architectures tailored specifically to your internal data models and workflows, emphasizing deterministic state machines and strict schema validation.
How do you prevent agents from making mistakes or hallucinating?
We restrict agent actions to typed tool interfaces, validate all outputs against runtime schemas before execution, enforce step budgets, and route high-risk actions to human approval gates.
Which models and providers do you support?
We build model-agnostic runtimes compatible with OpenAI, Anthropic Claude, Google Gemini, and open-source models (via Ollama / vLLM), allowing seamless model switching as economics and capabilities evolve.
Send us the engineering problem.
Tell us about your architecture, timeline, and current bottlenecks. We'll assess whether Stonewasp is a fit.