[BUSINESS ANALYTICS AND ML/AI]
Every transaction, ticket, and interaction your business records is a description of what already happened. Machine Learning and AI turns that record into forecasts (which customers will leave, which will grow, what demand looks like next quarter) and enables you to act ahead.
Churn probability · next 90 days
Forecasting churn in a gym application
[SOLUTIONS]
Customer segmentation • Churn and retention models • Customer lifetime value prediction • A/B Testing
Classify customers by behavior and profile, predict who's likely to leave and when, estimate what each relationship is worth over time, and recommend the specific action most likely to keep or grow it.
Demand and sales forecasting • Performance analytics • Price and revenue optimization
Demand forecast by product, location, and period, so capacity and inventory match what's coming. Performance analytics that isolate what's driving results. Price modeled against volume and margin before the change goes live, not after.
RAG • LLM and private LLM implementation • Training and deployment of purpose-built models
We build AI systems that stay yours: retrieval-augmented generation that answers questions from your own files, private LLM deployment inside your own infrastructure, and purpose-built models and agents able to perform value-generating tasks.
Is your business ready to implement AI? Check our AI readiness and integration services[WHY IT MATTERS]
Plenty of organizations have accurate models that nobody acts on: the churn prediction arrives after the retention budget is set, the demand forecast reaches operations too late to adjust capacity, the segmentation study sits in a folder while the commercial team runs the plan it already had. The analytics were never the problem. The problem is that the decision process was never built to receive them.
That's the work. We build the models into how the business decides: connected to the moment the decision is made and understood by the people using them, so the output is trusted rather than overridden. AI carries this further, putting answers within reach of the people who need them instead of routing every question through a single analyst who becomes the bottleneck.
Conclusions delivered into the moment and the workflow where they are needed.
We deploy AI-powered models where the return justifies it. We believe in parsimony: not making things unnecessarily complex.
Shared definitions, clear ownership, and one trustworthy set of data. Every capability added compounds rather than fragments.
[HOW WE WORK]
A churn spike that looks like a service problem is sometimes a competitor opening two blocks away, or a price move you didn't see. Because we work in market intelligence as well, our models can draw on competitive, economic, and geospatial context alongside your own records.
Business understanding first, then data understanding, preparation, modeling, evaluation, and deployment.
Models are delivered in working increments and refined against real outcomes. Performance is monitored after deployment and recalibrated as new data arrives.
Models are only as reliable as what feeds them. We build the pipelines too, the same capability that runs our data engineering practice.
Know more[USE CASES]
Segmentation (slides)
Churn model prediction (slides)
[APPLICATIONS]
Churn and lifetime value prediction, next-best-action engines, AI-assisted demand forecasting, and language models that let commercial teams query their own pricing and performance in plain language.
Renewal and churn models, customer risk profiling, automated document processing for policies and claims, and AI agents that resolve repetitive internal queries.
Demand and sales forecasting, dealer performance analytics, and AI-assisted processing of service records and warranty documentation.
Absorption and demand modeling, project performance analytics, and document AI applied to contracts, permits, and technical specifications.
Machine learning forecasts for macro data or for beneficiary targeting, program targeting models, and knowledge bases that make dispersed institutional documentation searchable.
[CROSS LINKS]
Allow our team to understand your needs and propose an action plan.
DMA Research & Data Analytics
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