Critical Propulsion
What We Build

We build what we run on.

Our AI-amplified delivery model isn't just how we work. It's what we help you build. Every engagement moves you toward the same agent-ready architecture that makes our teams fast.

01

Modernize the Data Estate

Agents running against fragmented or stale data make bad decisions fast. We re-engineer pipelines, unify fragmented sources, and build the real-time data foundations that AI agents need to operate with accuracy.
Pipeline modernizationData unificationReal-time streamingQuality governance
02

Build the API Layer

Agents need infrastructure that holds up under load and doesn't lock you into a single platform. We architect API-first environments that let agents, yours and ours, plug in, scale independently, and evolve without coupling to any single platform.
API-first architectureMicroservicesObservabilityScalable orchestration
03

Deploy Business Workflow Agents

The endgame. Purpose-built AI agents that automate your manual business processes, tuned to your domain, integrated with your systems, and governed by human oversight.
Workflow automationDecision supportProcess orchestrationDomain-specific agents
Agentic Delivery Adoption

Capability, not dependency.

We don't just hand over the systems. Your product, design, BA, QA, and engineering people work in the swarm with us, on your real backlog. Running agentic delivery becomes something your people already do, not something we hand them at the end. No platform to get stuck on. No lock-in.

A product engineer, not a forward deployed engineer.

A forward deployed engineer deploys someone else's product into your world. A product engineer builds around your business.

  • No platform to fit into. We build around how you already work.
  • Our loyalty is to your business, not a product roadmap.
  • We do this with you, not to you.
Read the argument in Insights

What you keep.

Everything the engagement produces stays with you.

  • Custom systems built around your business. You own the code.
  • A maturity curve across people, process, platform, and tooling.
  • A roadmap built for your environment, not a generic template.
  • A team already running agentic delivery on your real backlog.
What We Deliver

Senior teams. AI-amplified. Streamlined to deliver.

US-based senior experts. AI at every seat. Deliver faster within your current budget.

01

Premium US Talent

Senior consultants with Big Four and enterprise pedigree. Direct accountability, full context, working software in the first Pulse.
02

Agentic AI

Every human role is paired with dedicated AI agents covering backlog orchestration, code generation, test automation, and architecture review. The agents run continuously. They don't bill hours.
03

AI-Orchestrated Delivery

Our seniors don't just use Copilot. They orchestrate AI tooling into a delivery workflow that solo developers can't replicate. Prompts, quality gates, and feedback loops tuned to your codebase.
Results

How we measure what matters.

We don't inherit benchmarks. Every engagement starts with a baseline (your current velocity, your current cost, your current bottlenecks), captured in Week 1 and measured against every week after. These are the four metrics we track, and why.

Effective Capacity

Baselined in Week 1. Tracked every sprint.

Cycle Time

Time from backlog to production, measured at the feature level, not the story level.

Quality

Defect escape rate: what gets past the gates and what doesn't.

Week 1

Forecast Confidence; how accurate our weekly forecast is versus actual delivery, and how fast it converges.

What the research shows

The market is moving. The question is whether you're ahead of it.

40%
Enterprise AI agent adoption by end of 2026

Gartner projects 40% of enterprise applications will feature task-specific AI agents by the end of 2026, up from less than 5% in 2025. The teams building on agent-ready infrastructure now have a structural head start.

Source: Gartner, 2025

How We Forecast

Built to de-risk your decision

Our approach to forecasting means the picture gets clearer every week, not blurrier. We don't ask you to trust a projection. We show you the trajectory in real time, so the data makes the case before we do.

You'll see progress in Week 1. If the metrics don't move, the conversation changes. That's by design.

Why measure now

Your stakeholders are asking for AI proof, not AI promises.

Six months ago, "we're experimenting with AI" was an acceptable answer in the boardroom. It isn't anymore. The teams that can show measurable delivery gains are winning the next round of budget. The teams that can't are defending the current one.

Boards Want Numbers

Capex approvals are increasingly conditional on delivery telemetry. "We're moving faster" doesn't land. "Cycle time dropped from 14 days to 6" does. A baseline in Week 1 is how you earn the second conversation.

AI Credibility Closes Deals

Your enterprise clients are running their own AI readiness reviews, and your delivery telemetry is part of the scoring. Teams with defensible metrics close faster. Teams without them explain longer.

Trajectory Beats Projection

Executives don't trust projections from teams that can't show trajectory. When every week confirms or corrects the last, the conversation shifts from "is this on track?" to "what do we want next?"

Your Investment

We earn the next step

Our engagements are phased because each one has to earn the next. Each one delivers capacity targeted at outcomes with a clear investment range. If a phase doesn't earn the next one, we haven't done our job. No long-term lock-ins. No scope games. Just results that justify the next step.

FAQ

Common Questions

We work across custom application development, data engineering, enterprise AI advisory, headless API layer builds, and business workflow agent deployment. These are the same capabilities our own delivery model runs on. We build what we know works because we run on it ourselves.

Yes. Brownfield is a core competency, not an edge case. Agents that understand existing architecture are more valuable than agents that only work in greenfield. We assess the technical landscape, identify what needs to evolve for agents to deliver safely, and build iteratively.

Engagements are phased. Each phase has a clear investment range and targeted outcomes. Building on our Ignition Workshop approach, each iteration earns the next one. Results justify the next steps.

Agents are embedded at every role: code generation, code review, test authoring, backlog management, forecasting, and status reporting. Talent-dense consultants review everything before it ships. The model is not AI instead of humans. It is AI that makes each human on the team operate at increased capacity.

We baseline cycle time, deployment frequency, and effective capacity from Week 1. Every subsequent week is measured against that baseline. You see trajectory, not projection. Executives see numbers they can take to the business.

We focus on enterprise buyers where delivery complexity is high: professional services, financial services, healthcare, insurance, and private equity. Regulated environments are a fit, not a constraint. Our governance model is built for them.

See where you stand. Five minutes, ten questions, zero obligation.