Leasey
AI Solution Engineering

Build, evaluate, and ship LLM systems in production.

We design and implement AI systems end to end — from RAG and agents to MCP servers and cloud infrastructure on AWS and Azure. Grounded, observable, and cost-governed from day one.

Production, not prototypes

Evals gating every change

Cloud-native, private by default

chat.ts
// Grounded answer with retrieval + citations
const answer = await chat.ask({
  query: "What medications am I currently taking?",
  user: patient.id,
  scope: { permissions: "own_records_only" },
  retrievers: ["ehr", "notes", "labs"],
  evaluators: ["faithfulness", "pii_leak", "refusal"],
})

// -> { text, citations, trace_id, cost_usd, latency_ms }

Our trusted friends

Results

Numbers from systems in production.

4.2×
retrieval hit rate lift
>95%
extraction accuracy
~40%
support ticket deflection
Zero
cross-tenant data leakage
How it fits together

A production RAG pipeline.

Click a stage to see the code behind it.

Connect to your docs, tickets, warehouse, and databases. Versioned ingestion pipelines re-embed only what changed.

ingest.ts
// Versioned ingestion with source-version tracking
export async function ingest(source: Source) {
  const docs = await source.fetchSinceLastRun()

  for (const doc of docs) {
    const chunks = chunk(doc, {
      strategy: source.strategy,   // semantic | fixed | layout
      size: source.chunkSize,
    })

    await embed(chunks, {
      model: "voyage-3",
      cache: true,
      version: source.embeddingVersion,
    })
  }
}
Evaluations

Already have an LLM workflow? We’ll prove whether it’s working.

We audit existing systems for retrieval quality, faithfulness, safety, cost, latency, and drift — then fix the top issues and wire evals into CI so they stay fixed.

Explore evaluations
>95%
field-level extraction accuracy
3-5x
retrieval hit rate lift
<5%
hallucination rate target
30-60%
inference cost reduction
Platform

The tools we use — and why we pick them.

We work across model providers, orchestration, vector stores, evals, and cloud platforms. We pick the stack that fits your constraints, not ours.

OpenAIAnthropicAWS BedrockAzure OpenAIVertex AILangChainLangGraphLlamaIndexPineconeWeaviatepgvectorCohere RerankLangfuseMLflowLangSmithTerraformTemporalMCP
See the full platform
Process

How we engage.

01

Discovery

We map your data, workflows, and constraints. We agree on what "good" looks like in measurable terms.

02

Architecture

We design the system — retrieval shape, model routing, infra, guardrails — and the eval plan that proves it.

03

Build & Evaluate

We implement in iterations gated by evals on your data, not vibes or vendor demos.

04

Ship & Harden

We deploy to your cloud, wire observability and cost controls, and hand off with runbooks.

72-hour AI prototype sprint

Fixed-price, production-shaped prototype of your AI idea in a single weekend.

Private by default

VPC-isolated inference, scoped keys, audit trails. HIPAA and SOC 2 scaffolding on request.

15+ years of CTO experience

100+ projects delivered. We’ve shipped real systems with real traffic.

Leasey Operations Team

“We were able to scale our tech operations with a fraction of the cost and time it would have taken to build in-house.”

Leasey Operations Team

Ready to accelerate your tech growth?

Schedule your free consultation today and let's discuss how we can help your business scale efficiently.

Tech growth illustration
Ready when you are

Let’s ship your AI system.

Whether you’re scoping a new LLM product, hardening an existing one, or standing up the infra behind it — we’ll map the shortest path to production.

Email the teamOther ways to reach us