Pay, send your data, I build it.
Fixed price, no calls, no proposals. Pick what you need, pay, and a short form tells me exactly what to build. Delivered in days. These are the same systems that run my own companies.
AI Search Setup
Get found by Google and by AI models. I set up the indexing, schema, and an llms.txt layer so your site is read and cited, not skipped.
Get started →Content Engine
An automated pipeline that produces 30+ on-brand SEO articles a month, the system behind 200+ articles/month I run today.
Get started →AI Outreach Agent
An SMS or email outreach system with AI-drafted messaging, ready to send at volume. The engine behind 1,200 messages/hour.
Get started →Custom Web Automation Agent
An agent that operates a real web app the way a person would, running your repetitive workflow unattended where brittle scripts break.
Get started →Prompt Pipeline Tailor
Configure a local prompt engineering pipeline that converts any one-sentence idea into a structured Planner to Generator to QA brief, trains on approved results, and retrieves similar approved examples at generation time to improve future outputs.
Get started →Prompt Chain Builder
Decompose a task or existing specification into a multi-role sinc-format prompt chain with per-role JSON Schema contracts, gate definitions, and artifact-cap limits, then output a chain.json and step-by-step execution plan for your agent harness.
Get started →AI Architecture Review
You have AI in production but no map of where it is fragile, redundant, or costing more than it should. A fixed-scope paid audit: I read your stack, locate the failure modes, and deliver a written report with a prioritized fix list.
Get started →AI Incident Response Retainer
Production AI fails in ways no runbook covers: vendor model updates, prompt drift, edge-case cascades. An on-call retainer means I triage within one business hour, root-cause the failure, and ship the fix.
Get started →Vendor Exit Audit
Vendor pricing changes and model deprecations are not hypothetical. This audit maps your AI vendor dependencies, scores lock-in risk by component, and delivers a portability report: what you own, what you rent, and the exit path for each.
Get started →LLM Security Red-Team
Run an adversarial test campaign against your LLM application covering OWASP LLM Top 10 attack classes and relevant MITRE ATLAS techniques, then deliver a written threat model, a per-attack evidence record, and a prioritized control list.
Get started →Product Distiller
Ingest a batch of Claude or Codex session logs, extract the canonical procedure and product structure from observed execution traces, then compile a 15-artifact package including specification, replay harness, test plan, and a certification-gated completion record.
Get started →Agent Audit Trail
Set up a per-session run directory that links every assigned instruction to the agent that handled it, the artifact it produced, the QA verdict on that artifact, and the human decision that resolved any open issue, then verify traceability coverage at session close.
Get started →Persuasion Audit
Install a local MCP tool that checks any draft copy against 10 peer-reviewed persuasion and trust rules, returns a structured verdict with specific violation reasons and edit suggestions, and operates without network egress or model API calls.
Get started →AI Cost Optimization
Re-architect your AI stack with local models and smart routing. Cut the bill 70 to 80%, keep the quality, keep the data private.
Get started →Private AI Brain
A private, verified source of truth: a local-model RAG system trained on your data, QA-agent checked, that never leaves your infrastructure.
Get started →AI Token Cost Engineering
API bills grow before the architecture does. I audit your prompt design, model selection, and call patterns, then engineer the specification layer to cut token cost without rebuilding your infrastructure.
Get started →AI Observability Setup
You cannot debug what you cannot see. I instrument your AI pipelines with structured logging, drift detection, and alerting so failures surface before users report them.
Get started →LLM Eval Harness
When your vendor updates the model, you find out from a user complaint. I build an evaluation suite and regression harness so quality regressions surface in a test run, not in production.
Get started →Multi-Shot Reliability Layer
Instrument your LLM sampling pipeline with a math-verified policy layer that computes when majority voting improves results, when it fails by design, and what sample count to use, then validate the gate against your task mix with recorded decisions and evidence.
Get started →Agent Action Gate
Deploy a pre-action gate that forces each agent task to name its start state, end state, consequence ceiling, admissible actions, and done evidence before any tool runs, then verify the gate fires correctly in your environment with synthetic test cases.
Get started →Something bigger or custom?
If your build does not map to a card above, call me and I will scope it.
Pay
Pick a build and check out securely with Stripe. Fixed price, no surprises.
Send your data
A short form asks for exactly what I need to start. No meetings.
I build it
I build and run the system, the same way I built every production system before it.
Delivered
You get a working system in days, with everything documented and owned by you.