White-Label AI Development for Agencies — Your Invisible AI Engineering Pod

The client said yes. The kickoff is dated. And the options on the table are a $150K+ hire for AI work that's lumpy at best, a freelancer lottery where one missed deadline costs you the whole account, or a $99/mo white-label chatbot platform that can't do the custom work you actually quoted.

Demand hit agencies faster than talent supply: Upwork reports AI integration demand up 178% year over year, the fastest-growing coding skill on the platform. And MIT NANDA's 2025 research found that 95% of enterprise gen-AI pilots produce no P&L return — which is what happens when a build ships with no evals, no monitoring, and no acceptance criteria.

Your client won't blame the subcontractor. They've never heard of the subcontractor. That's the point — and the risk.

Every engagement produces five things: the delivered system (RAG chatbot, AI agent, LLM integration, or automation) deployed to your client's environment; an eval report in your brand — accuracy and groundedness scored against a threshold agreed at kickoff, the artifact that makes your agency look disciplined in the client readout; white-labeled documentation and a handover pack carrying your logo, your domain, your ticketing address; a monitoring dashboard your client can be shown live; and full IP assignment on final payment.

The margin math is plain: you quote your client $9,500 for a documentation chatbot. Our wholesale price is $3,500, delivered in two weeks. Your margin: $6,000 — without hiring anyone.

The confidentiality promise, in writing, not as a courtesy: NDA before discovery — we sign yours or send ours before any scoping detail changes hands. A contractual no-contact clause — we never email, call, or connect with your end clients, and we appear in client calls only if you invite us, introduced as your team. Your brand on all deliverables — reports, docs, dashboards, and the repo README if you want it. Non-solicitation both ways — we don't poach your clients, you don't poach our engineers. And clean invoicing — USD invoices from export-clean rails, net-7, no cross-border payment gymnastics for your bookkeeper.

Our business is agencies; poaching one client would end it.

The Nano Method, white-labeled: five stages your client never sees — only benefits from. Assess is a scoping call plus NDA, ending in a fixed-price quote and a delivery plan you can forward under your own letterhead. Pilot is the first fixed-price SKU — most agencies start with the RAG chatbot — paid upfront, with milestone dates in the SOW and SLA credits if we slip. Prove is the eval report, scored against the threshold agreed at kickoff — the deliverable your client actually sees, with your logo on it. Scale is a second project within 60 days converting into a monthly pod retainer: reserved capacity, one backlog, one standing call in your timezone. Operate means every deployed build carries an ops retainer — monitoring, evals, model updates — that you resell as your own AI maintenance plan: recurring margin on our pager.

The productized RAG Chatbot SKU is $3,500 fixed for a two-week build: up to 500 documents ingested, retrieval tuning, a chat UI or API endpoint, guardrails, and an eval suite run on 50 golden questions. You get the deployed chatbot, the eval report, white-labeled handover docs, and a 30-day fix window. Fine-tuning, more than 500 documents, and SSO/enterprise auth are named exclusions, priced separately.

Custom builds run at wholesale $30–60/hr, with the exact rate card by tier and role shared under partner NDA. Once the flow is steady, a monthly pod retainer reserves capacity, quoted after your first delivered project, billed monthly in advance on net-7 terms — pilot SKUs are 100% upfront. The typical agency markup we see on this work is 2–4x, and every deployed build carries an ops retainer, stated before purchase, because that's how production AI actually works.

White-label work is confidential by contract, so this page proves competence with artifacts, not name-drops: two internal demo systems with live eval dashboards, labeled as internal demo builds; a redacted sample eval report labeled as a sample deliverable with fictionalized data; a public GitHub org with tested, CI'd repos — the credential agency tech leads actually check; and the SLA terms themselves, rendered plainly: a 10%-per-week late credit, in the contract, not the marketing. We never fabricate logos or testimonials — where we don't yet have client proof, empty slots render as an artifact gallery instead.

Model layer: OpenAI, Anthropic, Google, plus open-weights models when data terms require it. Retrieval: pgvector, Pinecone, and Qdrant, with hybrid search and reranking. Orchestration: LangChain and LlamaIndex where they earn their keep, plain TypeScript or Python where they don't. Automation: n8n — open-source, self-hostable, enterprise-standard tooling. Delivery: Next.js and React frontends, REST or GraphQL APIs, deploys to Vercel, AWS, GCP, or Azure, and Docker throughout. Process: GitHub PRs your team can review, CI, versioned prompts, and eval suites in-repo. Every project runs under a signed DPA, with GDPR-clean processing for EU end-client data and a sub-processor list available on request.

Our delivery centers are in Cairo, Egypt — GMT+2/+3 — giving full working-day overlap with EU and UK agencies and afternoon overlap with US East Coast teams, in fluent English, on your tools if you prefer.