Spark, Build, Own.
An AI programme is only finished when your people can run it without us. Everything in our method works back from that.
Agree on where AI pays off, before anyone writes code.
Most organisations have more AI ideas than they can fund, and leaders who disagree about which ones matter. Spark settles that. We start with an Executive AI Workshop for your leadership team, then look closely at the data, systems and skills behind the use cases that came out on top.
The output is short and specific: which use case to build first, what it depends on, what could stop it, and a plan for the next 90 days.
You leave with
- A ranked shortlist of use cases with the value case for each
- A readiness review: data quality and access, systems, skills, risk
- A 90-day plan with owners and decision points
Put one use case into production, with your engineers on the team.
We build the first system together with your engineers. They pair with ours, review every design decision and write production code from the first week. That is slower for the first fortnight and much faster for the next five years.
We build on infrastructure you control. For banks and telecom operators that often means on-premises or in-country deployment, with models and data that never leave your environment.
What we build
- Retrieval (RAG) systems over policies, circulars and internal documents
- AI agents that take actions inside your workflows, with human approval points
- Bangla and English conversational interfaces
- Classical ML for fraud, churn and credit where it beats an LLM
- The data pipelines, evaluation and monitoring around all of it
Hand it over so it keeps working.
Handover is planned from the start. The engineers who built with us become the owners, and we train the wider team through the AI Academy. We write governance with your risk and compliance teams: who approves model changes, how outputs are monitored, what happens when something goes wrong.
After that we step back to an advisory role, available when you need a second opinion rather than a dependency.
You end up with
- A system your own team operates and extends
- Engineers trained on the patterns behind it
- AI governance and model-risk policies your auditors can follow
- Documentation written for the people who will maintain it
Common questions
Do we have to go through all three stages?
No. Some clients start with a workshop and stop there, others come to us with a use case already chosen and start at Build. But we design every engagement so that, by the end, your own team can run what was built.
Do you sell a platform or software licence?
No. We build on infrastructure and tools you choose and control, including on-premises deployments where data cannot leave your environment. There is nothing to renew with us when the engagement ends.
What do you need from our side?
An executive sponsor who can make decisions, two to four engineers who will work in the build team, and access to the data and systems the use case depends on. Without your engineers in the room, we will not start a build.
Can you work with our existing IT vendor?
Yes. Most banks and operators already have core-banking, billing or ERP vendors. We work alongside them on integration and keep the AI layer under your control.
Begin with one working session with your leadership team.
The Executive AI Workshop gives your leaders a shared view of where AI pays off in your business, what stands in the way, and what to do in the next 90 days.
About the workshop