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Claude consulting · Implementation · MCP
We design and build enterprise-grade AI on Claude: MCP servers, production agents, retrieval over your own data, and the cost controls that keep it affordable. Built inside your repos and your cloud, by people who were shipping production AI long before Claude existed.
Free 30 minutes. You leave with a rough budget range and the first thing we would build, whether or not you hire us.
Member of Anthropic's partner program. Every engagement is delivered by senior engineers, never juniors.
Surfaces
MCPCodeCoworkSkillsClaudeConnected
Notion
CRM
DB7 accounts flagged$0 at risk
CRM · renewalsSupport · 212 threadsDB · usage_90d
Grounded in your data. Cited, not guessed. illustrative run
The short version
Four things. We connect Claude to the systems it cannot see, build the parts that have to run unattended, prove it works before it touches a customer, and keep the bill under control. Everything ships inside your repos and your cloud, so you own every line.
MCP servers, API integration and retrieval over your own databases, so answers come from your records instead of a paste.
Production agents and Cowork routines with retries, fallbacks and alerting, so the work happens without anyone starting it.
Evals, guardrails and prompt-injection hardening. You find out from a test suite, not from a customer.
Caching, batching and model routing applied to the workloads actually costing money, with the savings modelled first.
The shift
Two or three people use it well, everyone else pastes prompts
→Wired to your data through an MCP server you control
Your systems are invisible to it, so every task ends in copy and paste
→Answers grounded in your real records, with citations
Answers sound right and cite nothing
→Agents that run on a schedule with retries, fallbacks and alerting
Work starts when somebody remembers to start it
→Evaluated before launch, monitored after
Nobody owns the bill and nobody can explain it
→Caching, batching and routing applied, so the bill stays sane
How we work with you
01
We design and ship the system, end to end, inside your repos and your cloud. Production standard, monitored, documented.
02
The recurring work runs on a schedule instead of waiting on whoever remembers. Set up in Cowork, with guardrails and a handover.
03
Your team learns to build the next one. We would rather be the team you call for hard problems than the team you cannot function without.
Enablement
Most Claude rollouts fail quietly. The tool gets bought, a few people love it, everyone else goes back to the old way, and the licence renews anyway. Training is what stops that.
We run hands-on sessions with your actual work in front of us, not slides. Engineers learn Claude Code against your repo and your conventions. Operators learn the Skills and routines built for their process. People leave having done the thing, not having watched it.
The receipts
We have shipped a number of AI products. This is the one built entirely with Claude Code and Cowork, and the one running a production MCP server in the cloud, so Claude uses it directly as a tool rather than through a browser.
Case study · Product, API and MCP server
An AI product-decision partner, designed and shipped end to end: a full web app, native integrations, a documented REST API, developer docs, and an MCP server deployed to the cloud. The screenshot is Mero registered as a custom connector inside Claude, with its tools and per-tool permissions live. Built with Claude Code and Cowork throughout, from empty repo to production.
Read the full case study
“Mero is our own product, so treat this as a builder's note rather than a client reference. I built it the way I would build yours: Claude Code from an empty repo, Cowork running the recurring work, a public REST API, and an MCP server in the cloud so Claude uses it as a tool instead of a website. Everything on this page is something I have actually shipped.”
How it works
01 · Consult
We map where Claude belongs, design the architecture and tell you what to build first. You keep the plan either way.
02 · Build
Scoped separately. We build inside your repos and your accounts, ship to production with monitoring, then hand you the keys.
03 · Handover
Docs, conventions and training, so your team can extend it without booking us again.
You own everything we build. Code, prompts, Skills, credentials and docs all live in your accounts. There is no platform of ours to stay subscribed to, and you can take it in-house tomorrow.
Access stays scoped and stays yours. The MCP server runs in your cloud on your credentials, and Claude gets tool-by-tool permissions you approve, so you decide exactly what it can read and what it can change.
What we charge
Two shapes. A scoped build, priced as a fixed project once we know what we are building. Or a retainer, when you want us owning the Claude architecture and training your team over months. We do not list prices because we have never quoted two of these the same. Scope drives the number, and scope takes one call to establish.
Model one
Priced as a fixed project once we know what we are building. One outcome, one number, agreed before anyone starts.
Best when you know the thing you want shipped
Model two
We own the Claude architecture, review the builds and train your team over months. Senior judgment on tap without carrying the hire.
Best when you are shipping continuously
Rough scope ladder Smaller to larger
A single, well-scoped piece. A good first engagement if you want to see how we work before committing to more.
Something customers or staff touch daily, built to survive real traffic rather than a demo.
Build and enablement together, so the system ships and your team can carry it forward.
If you are looking for a few hours of Claude help or a single prompt fixed, we are not the right fit and the call will waste your time. You will leave the first call with a range. Not a proposal, a range. Get a budget range on the call
Who you are hiring
Founder · Shipped with Claude · Ishan Vats
Claude Partner Network member. Builders and engineers who have delivered for 150+ teams, backed by three decades of combined engineering experience across enterprise AI.
Every build is tied to one number that matters to you: revenue up, hours saved, or churn down. If it does not move that number, we do not ship it.
What we build runs in production without babysitting, tested against your real workflow and fully documented. It stays stable long after we have handed it over.
Most clients come back for the next build, because the first one worked and the people behind it were easy to reach. We stay reachable after handover, not just during the project.
Your Claude bill
Teams ship the thing that works, traffic grows, and the invoice quietly becomes a problem nobody owns. We read where the tokens actually go, by project and by task, then fix the pattern causing it. These are Anthropic's published discounts, not our estimates, and most workloads qualify for more than one.
0%
Off cached input tokens when the same context repeats across calls. Long system prompts and document context are the obvious candidates, and almost nobody switches it on.
Anthropic published pricing0%
Off both input and output for anything that does not need an answer this second. Most reporting and enrichment work qualifies and nobody notices the delay.
Anthropic published pricingRouting
Send the easy majority of calls to a smaller model and reserve the frontier model for work that genuinely needs it. Usually the single biggest line-item win.
Architecture, not a discountA spend audit is a fixed-scope piece of work. We read your usage, model the savings, and give you the changes ranked by what they return. If the audit does not identify at least its own fee in annualised savings, we refund it in full.Get your Claude spend audited →
Read first
Everything we have written on putting Claude to work. Start here if you would rather read than book.
MCPWhat the Model Context Protocol is, and when your business actually needs an MCP server.
Read the guide →
SkillsTurn the SOPs nobody opens into workflows your team runs by name.
Read the guide →
CoworkThree ways to run scheduled AI work, and which one fits which job.
Read the guide →
StackThe practical automation stack when you want judgment inside a workflow.
Read the guide →
CompareWhere each one wins on real operational work, not benchmarks.
Read the guide →
CompareWhen to use which, and why most teams end up running two.
Read the guide →
ModelsWhat changed, and which workloads should move to it.
Read the guide →
ModelsWhen it is the right call and when it is overkill.
Read the guide →Before you book
By next quarter
Book a free 30-minute call. We will map what we would build first, what it would take, and whether you should build it yourselves.
If we are not the right team for you, we will say so on the call and point you to who is. No deck, no hard sell.
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