Engagement · Dedicated teams
Three to five senior engineers with a technical lead, running as one team against your roadmap. You set the priorities; they take the delivery risk off your engineering manager's desk.
Tell us what you want owned. The mix follows from that, and it can change once we are in the work.
2 backend · 1 full-stack · 1 platform · lead
A customer-facing surface — onboarding, billing, a new module — from schema to interface.
from $15,500 / month
2 AI/ML · 1 backend · lead · PhD review
An intelligent feature and everything under it: retrieval, evaluation, serving and cost.
from $18,500 / month
2 data · 1 cloud/DevOps · lead
The warehouse, the pipelines and the infrastructure they run on, plus the cost line.
from $16,500 / month
Quarterly term, 60 days' notice, two-week paid trial at the start like every other engagement. Full pricing sits on the services page.
This is the whole difference between a pod and a group of contractors.
Technical & Project Manager
20+ years
Runs delivery. Twenty years of shipping software across enterprise and product teams, most of it with distributed engineers on two continents.
Machine Learning Engineer
10+ years
PhD in Mathematics & Machine Learning. Reviews the modelling approach on every AI engagement before a line of production code is written.
Predictable enough to plan around, light enough that nobody spends their week in meetings about the week.
Every day
Fifteen minutes, in your channel, with your team. Not a separate offshore standup that gets summarised to you later.
Every Tuesday
The pod pushes back on scope before committing to it, which is the point of having a lead.
Every Friday
Working software, then a document. Both land before your Friday morning.
Every month
A senior lead from outside the pod reviews the code and reports to you directly, including what they did not like.
Median length of a pod engagement
Minimum handover at the end of any pod
Written status, every week, without being asked
Notice. Quarterly term, not annual
AI compliance platform
A self-hosted platform that audits contracts against GDPR, HIPAA and SOC 2 and returns cited, severity-ranked risk reports — with inference running on the customer's own GPUs, so no document leaves their network.
AI productivity platform
One workspace holding 33+ AI tools for writing, research and chat, with the accounts, subscriptions and infrastructure needed to keep them all running.
A pod has a technical lead who is accountable for delivery, and a delivery process run by Muhammad Tahseen on our side. With augmentation, that accountability sits with your engineering manager. Four individuals cost less; a pod costs less of your team's attention.
Entirely. You own the roadmap and the priorities. The pod owns how the work is broken down, sequenced and delivered against it, and reports back weekly in writing.
What shipped, what slipped and why, what is at risk, the decisions we need from you, and a burn-up chart. It is written to be forwarded to a board without editing. You get it every Friday by 09:00 ET.
Yes, with 30 days' notice in either direction inside the quarterly term. Growing typically takes 3–4 weeks to fill from the bench without lowering the bar.
Within the pod's working window, the pod. Overnight US coverage needs either your own rotation or a second shift, which we can staff and will price honestly rather than pretend a single team can cover 24 hours.
A handover period of at least three weeks, runbooks, architecture decision records and a walkthrough with whoever takes it on. No knowledge is held hostage — it is in your repository already.
Thirty minutes to scope it, a written proposal with a named lead and a composed team within a week.