Production AI Architecture

AI workflows that survive real work.

I help teams turn AI pilots into usable production workflows with the data paths, APIs, tools, retrieval, evaluation, approvals, deployment, and operations they need.

The hard part is rarely the prompt alone. It is deciding what the system may read, what it may do, how people review it, how failures are caught, and how the workflow stays safe after launch.

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Good fit

Agent workflows that need real tools and approval paths.
RAG and document ingestion over messy business data.
Model routing, evaluation, observability, and guardrails.
Backend/cloud architecture for AI products and internal systems.

Services

How I help

Production AI Workflow Audit

Map one workflow, identify the real production risks, and define the safest first implementation slice.

Agentic AI Pilot Rescue

Debug RAG, chatbot, or agent prototypes that looked good in demos but break under real data, users, or operations.

AI Workflow Build Slice

Build one useful end-to-end slice around real data, APIs, tools, approvals, evaluation, and deployment.

Fractional AI Architecture Support

Give founders and product teams senior AI/backend architecture support for vendor choices, evals, model routing, and implementation planning.

Delivery Partner Support

Support agencies and consultancies behind the scenes when AI delivery gets technically deep.

AI Evaluation and Operations

Set up practical checks, logs, review loops, cost visibility, and rollback paths so AI workflows can improve safely after they ship.

Method

From idea to production slice

1. MapWorkflow, owner, data, tools, constraints.

2. BoundPermissions, privacy, failure modes, human approval.

3. EvaluateTest cases, regression checks, confidence signals.

4. ShipOne working slice, observable and reversible.

5. OperateReview failures, control cost, improve safely.

Proof

Built in public where possible

Jevvellabs is my public surface for production AI architecture work. Instead of broad claims, the profile points to open-source and machine-readable evidence: Makakoo OS, Lope, Scoutica Protocol, 2md, A2A Ruby SDK, and current AI infrastructure work.

Profile and proof Machine-readable profile GitHub

Start small

Send one workflow.

If your AI pilot is stuck between demo and production, send me the workflow. I can usually spot the first real blocker quickly.

Message me on LinkedIn

AI workflows that survive real work.

Good fit