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AI Solutions

Production AI, not pilots that go nowhere

We build agents, copilots, and RAG systems that survive the move from demo to production — observable, evaluated, and grounded in your data.

30+Agents shipped
92%Eval pass rate
6 wksDemo → prod
// agent.runtime · run-7af3 live
search_kb
get_account
call_api
send_email
What we build

Six capabilities, deeply

From discovery to deployment — including the unglamorous parts most teams skip.

Agentic systems

Autonomous workflows that plan, call tools, and recover from errors.

Tool useMulti-stepGuardrails

Copilots & chat

Domain-trained assistants embedded in the apps your team already uses.

SlackZendeskIn-app

RAG over your data

Answers grounded in your docs, tickets, and knowledge base — with citations.

Hybrid searchRe-rankEval

Document intelligence

Extract, classify, and route invoices, contracts, and forms — at scale.

OCRSchemaValidation

Fine-tuning & distillation

Smaller, cheaper, faster models tailored to your domain and tone.

LoRASFTDPO

Safety & evaluation

Red-teaming, eval harnesses, and policy guardrails — before you ship.

Eval suitesPII filtersRed team
The build path

From scoped problem to production agent

We don't start from prompts. We start from the failure cases — then design the data, retrieval, and evaluation around them.

01

Scope & evals

Define the user task, golden examples, and success metrics first.

02

Data & retrieval

Ingest, chunk, embed. Tune hybrid search and re-ranking on real queries.

03

Agent & tools

Compose tools, plan loops, and guardrails. Test on adversarial cases.

04

Observe & iterate

Trace every run, score outputs, and improve weekly with real traffic.

// pipeline.rag

User query

"When does my renewal start?"

input

Embed + retrieve

Hybrid: BM25 + dense vectors

top-20

Re-rank

Cross-encoder, threshold filter

top-5

LLM + tool calls

Synthesize + call APIs as needed

plan

Guardrails + cite

PII filter, source attribution

verify

Stream response

With citations & confidence

output
Where it pays off

Six AI builds we've shipped this year

Each scoped to a measurable business metric — not vibes.

Support copilot

Deflect tier-1 tickets with grounded answers and safe handoff to humans.

6–10 wks 40% deflection

Contract intelligence

Extract clauses, flag risks, and answer "where in our MSA does it say…"

4–8 wks 95% precision

Sales research agent

Account briefs, intent signals, and outreach drafts — every morning.

4 wks 10× ramp

Invoice & form OCR

Schema-validated extraction with human-in-the-loop for edge cases.

3–6 wks 99% accuracy

Internal dev assistant

Codebase-aware copilot that knows your conventions, libs, and lint rules.

6 wks -30% PR time

Risk & fraud signals

LLM + classical ML hybrid scoring with explanations regulators accept.

8–12 wks SOC-2 ready
Toolbox

Model-agnostic, opinionated where it counts

We pick the cheapest model that passes your evals — and swap when better ones land.

Frontier APIs

ClaudeGPT-4oGeminiMistral

Open-weight

Llama 3QwenMixtralPhi-3

Vector / search

pgvectorPineconeWeaviateOpenSearch

Orchestration

LangGraphLlamaIndexDSPyInngest
Responsible AI

Built to be trusted, not just shipped

Every system we build comes with the same five things — because retrofitting them after launch is how AI projects die.

Eval harness

Golden sets, regression tests, CI gates

Full traceability

Every prompt, tool call, and citation logged

PII & policy filters

Pre- and post-call safety layers

Bias monitoring

Slice-based metrics in production

Human-in-the-loop

Tunable confidence thresholds

Data residency

On-prem, VPC, or sovereign cloud

Have an AI idea worth building?

Tell us the user, the task, and the success metric. We'll tell you whether it's a 4-week prototype or a 4-month build.

Scope an AI build