Modern AI and data platform
Consolidate warehouses, lakes and streams into one governed platform your teams will actually query.
Make enterprise data answer to the business
We build the data platforms, AI systems and governance that move pilots into production. Measured in quarters, not years.
Trusted by leading enterprises
Trusted by organisations across industries to turn data and AI into measurable business impact.
What we build
Five practices that ship together. Most engagements start with one and pull in the others as the platform earns trust.
AI product engineering
AI products built for the constraints of your operation, shipped with monitoring, retraining and a rollback path.
AI consulting
Where to start, what it costs and what it returns. Retrieval, evaluation and guardrails designed before anyone writes code.
Managed services
We run the platform after it ships. Lineage, quality contracts and access control that hold up when the auditors arrive.
Analytics solutions
Metrics your teams agree on, delivered into the tool where the decision actually gets made.
Where the work happens
The constraints differ by sector. The pattern does not: unify the data, prove one decision, then industrialise it.
Banking
Risk, fraud and regulatory reporting built on lineage that survives an examination.
Insurance
Underwriting and claims decisions supported by data the actuarial team will stand behind.
Financial services
Portfolio, treasury and compliance reporting on one governed platform instead of nine.
CPG and retail
Demand forecasting and assortment calls that reach store managers, not just dashboards.
Manufacturing
Predictive maintenance and yield analytics across plants that were never instrumented for it.
Healthcare
Clinical and operational data unified under controls your compliance team will sign off on.
How a programme actually runs
No twelve-month discovery phase. The first production workload ships while the wider platform is still being built.
Book a consultationDiagnose
Two to four weeks mapping your data estate, the decisions it feeds and the places where value is stuck.
Ends with a costed backlog, not a slide deck.
Architect
A reference architecture and delivery plan sized to your cloud, your team and the budget you actually have.
Reviewed with your platform and security leads before anyone writes code.
Industrialize
The first workload reaches production with tests, monitoring and a named owner on your side of the table.
We do not hand over a notebook and call it a system.
Scale
Platform patterns, enablement and governance, so the next ten workloads do not need us in the room.
Our success measure is how quickly you stop calling.
Work that reached production
Three programmes where the model, the platform and the people who run it all shipped together.
Aurelis Energy, Energy and utilities
One load forecast the grid planners actually trust
Nine regional forecasting spreadsheets became a single model service, retrained weekly and monitored in production alongside the systems that consume it.
- lower day-ahead forecast error
- A third
- planning cycle time
- 5 days to 1
Brightmoor Retail Group, Retail and CPG
Allocation decisions that reach the store floor
Demand signals now land in the replenishment system overnight instead of in a Monday morning slide.
600 stores on one demand signal
Kellner Werke, Manufacturing
Predictive maintenance on machines older than the cloud
Retrofitted sensor data joins decades of ERP history in one lakehouse, so maintenance gets scheduled instead of triggered.
A fifth less unplanned downtime
AWARDS & RECOGNITION
Earned for Impact
+ INDUSTRY RECOGNITIONSRecognition from leading technology platforms and industry organizations for the impact we create through AI, data and digital transformation.
GREAT PLACE TO WORK
Great Place To Work 2026-2027
2026–27
Certified for a great workplace culture in India.
1 / 14
We build on what you already run
No proprietary middleware and no lock-in layer of our own. Your platform stays yours after the engagement closes.
- Amazon Web Services
- Databricks
- Microsoft
- Qlik
“They shipped a working model in the first quarter, then spent the second one teaching our engineers to own it. Nobody else offered that second part.”
“Our governance story used to be a slide. It is now a system the auditors can query for themselves.”
“The forecast is not perfect. It is defensible, and the planners can see exactly why it says what it says.”
What we are writing about
Notes from engagements, published when we have something specific to say.
Applied AIJune 20268 min read
Why most AI pilots stall before production
The blocker is almost never model quality. It is ownership, evaluation and the absence of a deployment path.
GovernanceMay 20266 min read
A data contract is a staffing decision, not a schema
Contracts only hold when someone is paid to answer the pager the moment one breaks.
ArchitectureApril 202611 min read
Lakehouse migrations: what breaks in month four
Cost, not correctness, is what usually ends these programmes. Here is where the spend hides.
Applied AIMarch 20267 min read
Evaluating retrieval quality without a labelled set
Practical ways to measure a retrieval system when nobody has annotated your corpus.
Start with the diagnosis, not the platform
Four weeks, a costed backlog and a clear view of what your data can support. If the answer is that you do not need us yet, we will say so.
Book a consultationTell us what is stuck
A principal engineer reads every message and replies within two working days. If we are not the right fit we will tell you who is.
- hello@exponentia.ai
- Phone
- +91 22 6142 8800
- Offices
- Mumbai Placeholder address, replace before launchLondon Placeholder address, replace before launch