Ship the RAG systems, AI agents, and LLM features your clients are already asking for.
Senior engineers with YC and VC-backed company experience, deployed into your projects in 14-day sprints — white-label or alongside your team. You keep the client, the brand and the margin.
WE TAKE ON 4 NEW AGENCY PARTNERS PER MONTH
client query
route + decompose
hybrid search · top-k 8
3 tools called
grounded answer + citations
The AI work is already in your inbox. You’re quoting around it.
Your clients are asking for RAG systems, AI agents and LLM features. Most agencies pass, subcontract it badly, or stall the scope until the client goes somewhere else — not for lack of demand, but because the right people aren't in place.
Offshore teams cost more in rework than they ever save.
That is true of cheap teams. Ours are senior engineers who have shipped production AI at YC and VC-backed companies — they arrive with the judgment that prevents rework, not the rates that cause it.
Offering AI means hiring a six-figure engineer before you can sell a single project.
You sell the project first. We deploy into it in 14-day sprints. No bench payroll to carry through the slow months, no hire to justify before the revenue exists.
Nobody outside my team can be trusted in front of my client.
Then don't put us there. We work white-label under your brand and your process — or on calls beside you if you'd rather. The choice stays yours on every engagement.
Agency owners who once believed all three are now shipping AI builds under their own name.
The builds you've been quoting around.
Not demos. Production systems with evals, guardrails and observability — the parts that decide whether your client renews or blames you.
RAG systems
Retrieval over your client's real documents — contracts, tickets, manuals, claims — that answers correctly and shows its sources.
- Hybrid vector + keyword search with reranking
- Chunking tuned to the document type, not a default
- Citations on every answer, so the client can audit it
- Eval suite that catches regressions before the client does
AI agents
Agents that take real actions in your client's systems — booking, routing, updating records — with a human in the loop where it matters.
- Tool and function calling against existing APIs
- Approval gates on anything that writes or spends
- Retries, fallbacks and timeouts that fail safely
- Full run traces, so a bad output is explainable
LLM features
Drafting, summarization, extraction and classification shipped inside the product you already built.
AI CRM & automation
Workflow systems where the model handles the follow-up, the reminder and the routing.
Data & vector pipelines
Ingestion, embeddings and refresh jobs that keep retrieval from going stale after launch.
Dedicated engineers
Senior engineers embedded in your team, under your brand, for as long as the build runs.
Consult, scope, build, ship. Then we stay on.
You bring the scope. We tell you if it's real.
An RFP, a client request, a project you half-quoted and stalled on. We tell you what's buildable, what isn't, and what it costs.
- Honest read on whether the client's data supports the feature
- One sprint or two, said out loud rather than discovered later
- No charge, no obligation
Consult, scope, build, ship. Then we stay on.
You bring the scope. We tell you if it's real.
An RFP, a client request, a project you half-quoted and stalled on. We tell you what's buildable, what isn't, and what it costs.
- Honest read on whether the client's data supports the feature
- One sprint or two, said out loud rather than discovered later
- No charge, no obligation
We've already been the backend team on this exact setup.
Shipped as the engineering team behind other agencies, and directly for the operators who use them.
Rotation Match Network
Came to us as outsourced work through a US agency — after their client had already lost money on developers in the Philippines.
A secure workspace for clinical placements and compliance: students request rotations, preceptors review them, and admins verify documents in one place — with search across specialty, location and start date. We ran the go-to-market alongside the build, so the platform had supply and demand on it from launch rather than after it.
Auto shop CRM
US and Europe agencies had quoted this client $100K–$200K.
Shop OS covering check-in through invoice, with LLM-driven service reminders and SMS automation that follow up without a service advisor writing the message.
Boomzo
Scaled to 15 pincodes across the country.
Marketplace connecting users with verified home, salon, repair and real-estate professionals — provider onboarding, booking flows and coverage that expands pincode by pincode.
TechTrail DMC
Three API providers behind one booking flow.
Flight booking engine, hotel booking engine, itinerary builder and visa module for travel agents — each one live against a different provider's API.
Shivam Engineers OMS
Purchase orders arrived as PDFs and were retyped by hand.
Order management system replacing their spreadsheet. PO PDFs are read into structured line items by a model, then checked by ordinary code — quantity × rate has to reconcile with the printed total — before a person confirms them into live orders.
Senior engineers. Not a bench of juniors with a senior on the invoice.
The rework you've been burned by offshore comes from seniority, not geography. This is the part we don't compromise on.
Shipped production AI, not demos
Every engineer has taken LLM systems to production at YC or VC-backed companies — where a hallucinated answer had a customer attached to it.
You meet them before they start
No bait-and-switch between the sales call and the sprint. You talk to the engineer who will be in your repo.
Dedicated, with real overlap
Not split across five projects. We hold hours that overlap your working day, so review cycles take hours instead of days.
They stay after launch
The engineer who built it handles the bugs and build issues that surface once real users arrive.
Stack we work in
What agency owners ask first.
Yes. We work in your repo, under your brand, inside your process — your client never needs to know we exist. If you'd rather introduce us as your AI team on calls, that works too. You decide per engagement, and you can change your mind.
The rework you paid for came from seniority, not geography. Every engineer here has shipped production AI at YC or VC-backed companies, you meet them before the sprint starts, and scope is locked in writing on day 2 — so 'we thought you meant something else' stops being possible.
That's the normal case. We make the architecture decisions, document what we built and why, and walk your team through it in the final days of the sprint. The goal is that you can maintain and sell it without us — and call us when you want the next thing built.
Only if you ask us to. Default is that everything goes through you and your client sees your brand on every deliverable.
A working RAG system over a real document set with evals and citations. An agent that calls your client's existing APIs with approval gates. An LLM feature inside an app you already built. Not a full platform from zero — and we'll tell you on the consultation if your scope needs two sprints instead of one.
We stay on for bugs and build issues, so you're not left explaining a broken deploy to your client. If there's more to build, we scope the next sprint. If there isn't, you owe us nothing until there is.
We take on 4 new agency partners a month, so it depends on when you ask. Book the consultation and we'll tell you the real date, not an optimistic one.
Want to stop turning down AI projects?
Bring the scope you’re unsure about — an RFP, a client request, a half-quoted project. We’ll tell you what’s buildable, what it takes, and whether it fits in one sprint. No charge for the call.