Cross-functional Data & AI pods
Each pod combines data engineering, ML engineering, analytics engineering, and tech leadership in one tight unit. You do not have to assemble a team yourself or chase four vendors to get one project done.
Agile Team Augmentation & Talent
Senior Data & AI pods, ready to ship next week.
Cross-functional pods that integrate with your team, deliver from the first sprint, and scale up or down without the usual hiring overhead. Pre-vetted specialists, real engineering rigor, and a model that flexes around your roadmap, not the other way around.
Borrow expert teams. Skip the hiring marathon.
Hiring senior data and AI talent is brutal. Job specs sit open for months. Your best engineers spend half their week interviewing instead of building. New hires take a quarter to ramp. By the time the team is finally complete, the project that justified the headcount has pivoted, slipped, or quietly been shelved.
Our pod model gives you a different option. A pre-built, cross-functional Data and AI team that integrates with your existing engineers in days, ships meaningful work in the first sprint, and scales up or down as your roadmap moves. No CV roulette. No six-month onboarding. No hiring-freeze risk. Just senior people doing senior work alongside your team.
The talent gap is killing your roadmap
Every CTO and CDO has the same story right now. More high-priority data and AI work than the team can possibly absorb. A hiring funnel that produces one good candidate every couple of months, at salary expectations that keep climbing.
Generic staff augmentation has not solved this. Body-shop contractors arrive without context, need weeks of hand-holding, and disappear at the end of the contract along with everything they learned. Big consultancies arrive with armies of juniors and slide decks. Neither feels like a real teammate.
What companies actually need is a pod of senior, pre-vetted specialists. People who understand the modern data and AI stack, can plug into existing rituals and codebases, and can flex up or down as the work demands. Without the rehire-and-let-go drama every quarter.
Pods that act like teammates, not contractors
Pre-vetted senior specialists
Every engineer on every pod passes our internal vetting. Technical, communication, and judgment. No CV roulette. No surprises on day three. No junior hidden behind a senior rate card.
Shipping in sprint one
Pods join your existing rituals: standups, planning, retros, code reviews. They contribute to the same backlog your team already works from. The first sprint produces real, merged, deployed work. Not onboarding documents.
Scale up and down without friction
Need to double the pod for a quarter and shrink it again? No problem. We handle staffing, ramp, and hand-offs. Your roadmap flexes without a hiring cycle attached to every change of direction.
Where pods make the biggest difference
The situations where a cross-functional pod ships more than a hiring sprint ever will.
Roadmap acceleration
When the backlog is stacked higher than the team can possibly clear, a pod plugs in alongside your engineers and ships the next several quarters of work. Without you having to hire.
Critical project surge
Time-boxed pods for high-stakes initiatives: a regulatory deadline, a board commitment, a launch. Senior firepower for one or two quarters, then off the bench.
Burnout & bus-factor relief
Step in to take pressure off an over-stretched in-house team before key people leave. With the seniority to contribute from day one, not to need constant ramp.
Lakehouse & data platform build
Stand up a modern data platform end to end: ingestion, modeling, governance, BI. With a pod that has built dozens of them and will not reinvent every wheel.
MLOps platform build
Build the MLOps backbone (feature store, model registry, deployment, monitoring) that turns your data scientists from notebook authors into shipping engineers.
Internal data product teams
Bootstrap a data-products team inside your organization. Hand it off to a permanent in-house leader once the patterns and culture are in place.
Legacy warehouse migration
Drive a wave-based migration off legacy warehouses with a pod that has done it before. Without freezing feature work on the systems you are replacing.
Pipeline modernization
Rebuild brittle, undocumented ETL into modern frameworks while keeping the lights on. The business never feels the cutover.
Tooling consolidation
Reduce the sprawl of overlapping data tools without breaking the workflows people actually depend on.
GenAI pilot to production
Take your most promising LLM or RAG (retrieval-augmented generation) pilot out of a notebook and into a production system that legal, security, and ops are all comfortable with.
ML use-case discovery & delivery
Embed an ML pod with a business unit to find, scope, build, and ship the highest-ROI use cases. Not a slide deck of possibilities.
Production AI hardening
Take models that already exist but are not trusted in production, and put monitoring, retraining, and guardrails around them. So they can actually be used.
Interim heads of data / AI
Senior interim leaders who can run a function while you search for a permanent hire. They leave the team in better shape than they found it.
Tech-lead embedment
Embed a senior tech lead inside an existing team to raise the bar on engineering practice, code quality, and delivery cadence.
Global talent supporting your growth
With 15+ global talent hubs, your time zone and budget are covered
Americas
Brazil
Argentina
USA
Canada
Mexico
Europe
Portugal
Spain
UK
France
Germany
Poland
What pods deliver for your business
Shipping in the first sprint
No three-month ramp. Pods join your standups, your repos, and your backlog from week one. Merged, deployed work follows shortly after.
Pre-vetted specialists, no CV roulette
Every engineer is technically and culturally vetted before they ever land on your team. Senior people doing senior work, not a job board on a rate card.
Scale up and down, no rehire drama
Flex the pod with your roadmap. No layoffs when a project ends. No hiring sprint when one expands.
Teammates, not contractors
Pods integrate with your rituals, your tooling, and your standards. They leave behind documentation, tests, and a team that can keep going without them.
Knowledge that stays after we leave
Every engagement includes deliberate knowledge transfer. Pairing, docs, reviews. Your in-house team is stronger after the pod is gone, not weaker.
Add senior firepower without the hiring marathon.
Tell us where you are stuck. We will scope a pod that fits your roadmap, your stack, and your timeline. It can start in days, not quarters.
Scope a pod for your team