Every enterprise runs on a stack of decisions: which platform the business runs on, where the data lives, and how much of the decision-making can safely be automated. Our work sits across all three.
We do a lot of things. Today we lead with three.
Microsoft Dynamics 365
Finance & Operations and Customer Engagement — implementation, rollout, upgrade and application management. We treat the Copilot layer as part of the platform rather than an addition to it: an ERP or CRM implemented today should have AI in the workflow from day one, not retrofitted later.
Data engineering and data science
Platforms, pipelines, lakehouses, feature stores and models. This is the least visible layer of the stack and the one every AI claim eventually rests on. If the ground truth is wrong, everything downstream is confidently wrong.
AI and ML, in production
Evaluated, observable, and carrying an outcome — not notebooks, and not pilots that never graduate. We have delivered more than twenty AI and ML projects in the last twenty-four months, and around seventy per cent of the team are product engineers rather than generalists.
The reason these three and not another three is that they are one chain rather than three bets. Dynamics 365 generates the enterprise data. Data engineering makes that data usable. AI and ML turn it into a decision somebody acts on. A firm that only does the third is guessing at the first two — the failures rarely happen in the model; they happen in the ground truth underneath it.
The rest of the stack
Alongside the three, we deliver:
- Oracle — EBS and Fusion: implementations, upgrades and ongoing support.
- SAP — delivery and support across the core enterprise modules.
- GCC advisory — helping organisations set up and scale global capability centres in India.
- Specialist talent — placing hard-to-find engineers where they are needed. Several of our strongest client relationships began exactly this way.
- Products — WorkWeave, BetterSDLC, and solutions for observability and resource optimisation: what your estate is actually doing, and what you are paying for but not using.
How we deliver
Most engagements open with a four-week proof of technology on production systems and real data, ending in a go or no-go. Week one, we agree in writing what success looks like; week four, there is a decision. Four weeks is an inexpensive way to answer an expensive question.
Ongoing work is structured as PODs: small, stable teams accountable for a defined result rather than a filled seat.
Securely and reliably
The last thing to say is the one that underwrites all of it. Whatever we deliver — an ERP rollout, a data platform, a model in production, a placed specialist — we provide it securely and reliably: security engineered in from the start rather than audited in at the end, systems observable in operation, and support that stays dependable long after go-live.
That is the standard everything on this list stands on.