A live AI system your team owns. In production in under 12 weeks. The same people who scope the problem write the code.
Four service pillars. One firm. The people scoping the work are the same ones writing the code, so nothing gets lost in translation and nothing gets quietly rescoped.
A discovery workshop to find and rank the right AI use cases. A co-build workshop to prototype the top pick on your real data. Run both, or start with whichever fits where you are. You walk away with a scored shortlist, a working prototype, or both, and a concrete next step.
Production software with AI embedded from day one. Apps your users log into, APIs that plug into your stack, pipelines that keep models fed, and agents that take repetitive decisions off your team.
AI engines don't know your brand exists unless your content tells them. We audit where you're invisible, close the gaps, and keep the loop running so you appear in the answers and stay there.
Campaign assets, landing pages, and brand systems on a build-shop cadence, not an agency retainer. AI-powered workflows where it helps, human judgment where it matters.
Three phases. Clear deliverables at each step. No open-ended retainers.
We figure out what's worth doing and what's not. You get a clear picture of feasibility, cost, and timeline before any budget is committed. No surprises at week six.
We build the thing. A working product real users can interact with, not a demo. Scope is locked. One use case, done well. This is what you show investors or put in front of customers.
Your team owns it. We document everything, train your people, and make sure it runs without us in the room. You keep the code, the system, and the knowledge.
You know what AI can do. You don't have senior AI engineers on payroll. That's where we come in.
Founders and product leads who need senior engineers to ship v1, or to retool an existing product around AI without tripling headcount
Domain experts without a technical team. You bring the problem, we bring the build.
Speed without headcount. Ship AI this quarter. Hire if you want to, after it's working.
Stop researching. Start building. You don't need more information. You need a working product.
| Dimension | Management Consulting | Dev Shop | Kobo |
|---|---|---|---|
| Outcome | Roadmap + recommendations | Technical build per spec | Production system with measured ROI |
| Timeline | 2 to 4 weeks (report) | Varies (no scope discipline) | Discovery + scoped plan in 2 to 3 weeks. In production in under 12. |
| ROI Accountability | Estimated in deck | Not scoped | Measured against Phase 1 estimates |
| Data Validation | Assumed adequate | Your problem | Audited in Phase 1 |
| Handoff | Report delivered | Code delivered | Trained team + documentation |
Discovery and planning wrap in 2 to 3 weeks. The full project is scoped to complete under 12 weeks, from discovery through launch. Complex builds can run longer, but we lock the timeline in Phase 1 so you know before committing build budget.
Yes. We audit integration complexity in Phase 1 before any build budget is committed. Legacy system integrations can add a couple of weeks to the engagement. We scope that cost before you approve Phase 2.
The handoff is part of the engagement. We train your operators, document the system, and deliver a production readiness checklist before we leave. If post-launch support is needed, we scope that separately.
Gartner found that at least 50% of GenAI projects were abandoned after proof of concept due to poor data quality, escalating costs, or unclear business value. McKinsey's research puts successful AI scaling at only 15 to 25%. The pattern is the same: scope grows unchecked, data problems surface mid-build, and no one owns the decision-making. Kobo's Phase 1 surfaces all three before build budget is spent.
The same people who run discovery and scope the plan are the ones who build and ship. No handoff to a junior team, no telephone game between a strategist and a developer. Scope drift, miscommunication, and mid-build surprises happen when planning and building are separate teams. We don't separate them.
Three things. First, do they build or just advise? A deck doesn't tell you if the product works. Second, do the same people scope and build? Handoffs between teams are where projects go sideways. Third, do they lock scope and timeline before you commit build budget? If they can't tell you what you're getting and when, you're funding their learning curve.
You can get surprisingly far with AI coding tools. But there's a difference between a prototype that works on your laptop and a production system that handles real users, real data, and real edge cases. If you need something your team or customers rely on daily, you need someone who's shipped that before.
That's exactly what discovery is for. We don't walk in assuming AI is the answer. We map your operations, identify where AI has real leverage, and tell you honestly if it doesn't. A clear 'not yet' in 2 to 3 weeks is worth more than a six-month project that proves the same thing.
Most failed AI projects didn't fail because of the technology. They failed because nobody locked the scope, picked the right use case, or owned the outcome. We do that before build starts. That's the difference between a project that ships and one that stalls.
Less than hiring a senior AI engineer for a year. More than a freelancer who disappears. Every project starts with a scoped plan and a locked price. You know the number before you say go.
That's what Phase 1 is designed to prevent. We invest 2 to 3 weeks upfront to make sure the scope is right before build starts. If something genuinely changes mid-project, we'll talk about it openly and re-scope together. But we don't let scope creep quietly — if the plan changes, the timeline and budget conversation happens before the code changes.
Tell us what you're trying to solve. We'll tell you if we're the right fit.
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