Five practices. No practice we can't back with a track record.
Each service below is staffed by people who've done the work before, not a slide of capabilities we're hoping to grow into.
Software & product delivery consulting
Most enterprise software programs don't fail on code quality. They fail on delivery governance: unclear ownership, sprint cadences that drift from business priorities, and reporting that surfaces risk too late to act on. We run full-lifecycle delivery governance across Agile, Waterfall, and hybrid models (sprint planning, backlog discipline, stakeholder reporting, and UAT sign-off) structured around your existing PMO rather than replacing it.
Operating model: the delivery lead who scopes the engagement in week one is who you talk to for the life of it. The team scales to program size, the point of contact doesn't change.
Technical recruitment & team augmentation
Growing engineering organizations need capacity that scales with roadmap commitments, not with hiring cycles. Our recruitment practice sources and vets engineers, developers, and project managers across web, mobile, and cloud disciplines for U.S. teams, backed by a dedicated delivery network, with direct experience placing talent against Fortune 500 and mid-market contracts.
Operating model: individual specialists, dedicated pods, or full delivery teams (full-time, contract, or contract-to-hire) with delivery oversight built into the placement, not a resume hand-off and a wave goodbye.
Applied AI & data
Most enterprise AI initiatives stall at the trust gate: stakeholders won't act on a prediction they don't understand the confidence of. Our data practice covers the operational foundation organizations need first (SQL-driven reporting, Tableau and Power BI dashboards) and layers in machine learning advisory built around model evaluation, calibration, and honest uncertainty communication.
Where we fit: organizations running their first rigorous AI deployment, not their fiftieth cheap one.
Digital transformation & DevOps
Ad-hoc delivery process is invisible right up until it's expensive: missed releases, unplanned rework, and status reports that arrive after the decision they should have informed. We introduce Agile and DevOps discipline incrementally, embedded into how your teams already operate, with release cadence and delivery pipelines designed to outlast the engagement instead of reverting six months after we leave.
Operating model: a phased rollout against your existing process, with the habits, not just the tooling, handed off before we go.
Program & account management
Enterprise stakeholders rarely lack information. They lack one trustworthy source of it. We run recurring sprint and account reporting, delivery governance, and escalation management as a standing function: burn-down data, status reporting, and risk visibility delivered on a cadence your leadership can actually plan around, not chase down.
Operating model: a named point of accountability for every program, with a defined escalation path agreed before the engagement starts, not improvised when something goes wrong.
Built to plug into how enterprises already run programs
We don't ask you to adapt to our process. Every engagement is scoped against your existing governance model: reporting cadence, escalation structure, and sign-off authority defined up front, in writing, before work starts. Communication runs on your cadence, not ours: weekly, sprint-aligned, or steering-committee-driven, whichever your organization already runs on.
Questions we get before an engagement starts
What's the difference between staff augmentation and a dedicated delivery team?
Staff augmentation places one or more people directly into your existing team, working under your management and process. A dedicated pod is a self-contained unit (engineers plus a delivery lead) run against a scope we help define, reporting to your stakeholders on an agreed cadence. Most engagements start as augmentation and evolve into a pod once the scope is clear.
Do you support contract-to-hire?
Yes. Placements can be full-time from day one, contract with no conversion path, or contract-to-hire on terms agreed before the engagement starts. We'd rather set conversion terms up front than negotiate them after someone's already embedded with your team.
Who actually owns delivery once the engagement starts?
A named lead, not a rotating account manager. That person is who you talk to for status, risk, and scope questions for the life of the engagement, whether the team is one person or a full pod.
Do you only work with enterprise clients?
No, we work across Fortune 500, mid-market, and startup engagements. The delivery model doesn't change much with company size; what changes is how much existing process we're plugging into versus building from scratch.
How is pricing structured?
Staffing engagements are typically billed per role: contract, contract-to-hire, or a direct placement fee. Delivery and AI engagements are scoped per program, usually time-and-materials or a fixed-fee milestone structure depending on how well-defined the requirements are going in. We quote after a scoping conversation, not before one.
What happens if a placement or engagement isn't working out?
We'd rather hear that early. Every engagement has an agreed escalation path from day one, and for staffing placements specifically, replacement terms are set in writing before the placement starts, not improvised if something goes wrong.
Not sure which practice fits?
Most engagements start as a conversation about the problem, not the service line. Tell us what you're stuck on.
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