AI enablement

AI shipped, not another committee.

We're a swarm of humans and AI agents at Mokko Labs, led by Mitesh Shah. We bring superhuman execution to the work; he's your accountable lead on every engagement. We embed with your CEO or AI lead for about 10 hours a week and help your organization actually run on AI: real workflows, sensible spend, guardrails sized to the risk.

Email Mitesh

Two client slots. One accountable lead. A swarm behind him.

The problem

Most organizations have bought the AI tools. Far fewer have changed how work gets done.

When AI gets serious, many organizations add headcount. Coordination grows with it, and progress can stay in pilots and planning.

AI has made building fast. The bottleneck now is how good your decisions are. Good decisions come from a small group thinking clearly together, with the authority to act. A small group with the right stack can decide and ship faster.

How we work with you

One swarm — humans and AI agents working as one. Mitesh leads on your side; we share the depth together.

We report to one person

You, the CEO or the AI leader — one clear line of accountability.

About 10 focused hours a week

We bring superhuman execution to those hours — the same swarm that builds, reviews, and ships — so they go much further than in a traditional engagement.

Engagements are scoped as 90-day outcomes

Not hours. We agree up front what ships and what changes.

Prove it in the product

We read the code and run the flow. A green test is a clue; working software is the evidence.

Two clients at a time

We take two clients at a time. Mitesh is your accountable lead on each, with the same swarm on the work from start to finish.

What we do

1. AI enablement across your org

Get AI into real work across engineering and the rest of the business.

AI spend that's sensible and pointed at outcomes, not seat sprawl.
Agents and bots built into your team's actual workflows.
A safe path for non-engineers to propose changes as PRs, tagged by blast radius: low-risk changes move fast, while anything touching security, privacy, money, or production infrastructure gets extra review.
Teams trained to keep going after we leave.

We've rebuilt products solo with AI agents, shipping features without line-by-line code review and catching agent mistakes before they land.

We've led AI rollouts where everyone from the CEO down ships code through pull requests — some through a Git setup, some through cloud agents.

Team members outside engineering build working feature simulations in tools like Replit to prove an idea works. Then we absorb what works and implement it properly in production.

We run this in production: a dedicated review agent tags every pull request by blast radius, so low-risk changes from anyone on the team ship fast and high-risk ones get a senior look.

We don't chase token spend for its own sake. Teams start on basic subscriptions, move to premium seats when the work warrants it, and unlock extra spend in graduated steps. When usage looks unusual, we check it: is it the right agent for the problem, or a genuine need for more spend?

2. AI continuity

Your team built something with Lovable, Replit or another AI tool. Now it's stuck, or it took off and has to be production-ready.

Rescue a stalled build, or harden a successful MVP: architecture, auth and data, real-flow testing, monitoring.
A clean handoff your team can own.

We haven't published a rescue case study yet — this is what we offer today. We rebuild products with AI agents, ship without line-by-line code review, and catch agent mistakes before they land.

3. IDEA Loops (and training)

Insight, Design, Engineering and Analysis in one focused working session. We build something concrete, learn from it, and decide what's next: ship, iterate, pivot, or stop. Most loops run 1–6 hours and close within 72 hours with a written record.

We run loops on your hardest product or operations question.
Then we train your people to run them themselves.

Read the IDEA Loop framework

Example 90-day outcomes

Illustrative only. We define yours together in the first conversation.

An AI intake or triage agent live in one real workflow, with a human in the loop.
AI tooling consolidated, spend down, and usage up across teams.
A vibe-coded MVP taken to a reviewable, production-ready release.
A risk-tiered process that lets non-engineers contribute safely.

Why us

We've built the thing ourselves. At CodaPet, Mitesh built the MVP solo, then grew and led a lean engineering team. The business now does $8.4M in annual sales with 100+ active vets. Mitesh leads engineering there and reports to the CEO.
Banking software experience. We built a React design system for Alogent's banking software suite, plus a next-generation banking demo built on it — product and UI design for banking software.
AI product engineering. On Frndo, an AI companion app, we've done hands-on work on latency and memory performance. The engagement is confidential — we won't share metrics on this page.
Founder and fractional CTO. Founding engineer on Route Exchange, co-founder of Route (exited), and fractional CTO at Konscious House of Brands since 2021, supporting e-commerce brands.
20+ years building software, mostly at startups where every tool had to pull its weight.

Where this works best

A good fit if:

You have a mandate to change how the company works and how decisions get made.
You report to, or work directly with, the CEO or the named AI lead, with authority to act.
You want one accountable senior lead and a capable swarm, with depth that stays on the work.
You’re in insurance, banking, credit unions, or insurtech — industries we’re focused on.
You’re a new Chief AI Officer or Head of AI with a mandate and ready to build.

Engagement

From $10k/month for about 10 focused hours a week, scoped around a 90-day outcome.

Tell us about the AI initiative you're driving.

Email us the short version — we'll tell you honestly whether we can help, and what we'd aim to ship in the first 90 days.

Email Mitesh