A 30-day embedded program that turns AI from one developer's side hustle into your entire team's default workflow.
Developers experiment with AI tools individually. But what works for one person rarely scales to the whole team. The gap between personal productivity and organizational impact is where most AI initiatives stall.
Sound familiar?
If you can't measure AI's impact, you can't scale it. And if only one person on your team knows how to use AI well, your bus factor is one. We fix both problems.
Our engineers embed with your team for 30 days. They build real features using AI-augmented workflows on your actual codebase. Your team learns by doing — not by watching slides.
We pair-program with your team on real delivery tasks using AI-augmented workflows. No toy projects. You see working code in your repos from day one.
"They have ensured the timely and impeccable execution of all assigned tasks."
— J. Greenwood, Managing Director & Founding Partner, Law Firm
Verified on ClutchWe train 2–3 internal champions, document every workflow, and leave behind a playbook your team runs independently — and keeps improving.
"Their knowledge and experience were instrumental to the project's success."
— Evelyn Ackah, Founder & Managing Lawyer, Ackah Business Immigration Law
Verified on ClutchWe define success metrics on day one — commit velocity, PR cycle time, adoption rates — and track them weekly. You get a dashboard, not a feeling.
"The PM was on our side for most of the time, but they delivered everything on time, and everyone on their team was responsive."
— Mateusz Piwnicki, CEO, Software Agency
Verified on ClutchA clear, month-long path from scattered AI experiments to team-wide adoption.
We integrate with your existing tools — GitHub, Slack, Jira, your IDEs — and work inside your real codebase. No sandboxes. No disconnected exercises.
"We are happy with the output and are currently using the screens and the prototype to seek investment."
— Aaron Braich, Co-Founder, Toggled
Verified on ClutchMap current workflows, tooling, and AI maturity across the team. Interview developers and leads. Establish quantitative baseline metrics (PR cycle time, commit velocity, defect rate) to measure impact later.
Define AI usage standards: when to use AI, how to review AI-generated code, prompt libraries for your stack, and CI/CD integration points. Tailored to your tech stack and team culture.
Our engineers embed in your daily workflow. Pair programming on real features. Code review with AI. Repo and environment configuration. Champion coaching sessions run in parallel.
Compare weekly metrics against your baseline. Deliver a best-practices playbook. Recommend a rollout strategy for the wider organisation. Schedule a 30-day follow-up.
AI systems we put in production. These run in front of real users every day.
A conversational commerce platform where the AI is trained on the client's product catalog. Customers ask questions in natural language, browse products visually, add items to cart, and check out — all within one chat interface. We built the training pipeline, retrieval system, and commerce integration.
Fuzzy needed a scheduling tool that lives inside Google Calendar. We built a browser extension where users create meeting polls, invite participants, vote on time slots, and auto-generate the calendar event when everyone agrees. The recommendation engine suggests optimal time slots based on invitee availability.
An immigration law startup wanted to automate eligibility screening and form preparation. We built a RAG pipeline over immigration policy documents, fine-tuned a model for form extraction, and created an end-to-end system that processes applications in minutes instead of hours.
Our engineers join your Slack, standups, and PR reviews. Not slide decks and Zoom calls. You get hands-on expertise inside your actual delivery pipeline.
Antagosoft adopted these same AI workflows across our own engineering teams. We know what works because we do it every day ourselves.
Champions, documentation, tooling config, and a metrics dashboard — all handed over on the last day. Your team keeps the capability and keeps improving it.
Most teams report measurable velocity gains within the first two weeks. Full programme metrics are compiled in week 4.
No. We integrate with your existing repos, IDEs, and CI/CD pipeline. Assessment during week 1 determines the best-fit tools for your stack.
You keep full control of priorities and backlog. Our engineers embed in your workflow and report to your tech lead. We handle coordination and programme management.
We schedule a 30-day follow-up to review metrics and troubleshoot blockers. Your internal champions continue driving adoption using the runbooks we leave behind.
Book a free 30-minute consultation. We'll assess your current state and outline a concrete plan.