Data science consultancy
Data science for organisations that need clear models, honest analysis, and findings their teams can act on with confidence.
First call
Free conversation to define the question
Plain language
Every model explained without jargon
Your data
Analysis built around your own sources
Working sessions that translate model output into options, trade-offs, and a next step your leadership can sign off.
We profile your datasets, surface quality gaps, and show where the signal is strong enough to build on.
Forecasts and classifiers designed around your use case, validated against holdout data and documented end to end.
Clear write-ups on which factors drive outcomes, so stakeholders can trace every recommendation back to evidence.
A/B tests and quasi-experiments planned with sample sizes and success criteria agreed before any data arrives.
Repeatable extraction, cleaning, and scoring jobs so the analysis refreshes without manual rework.
Working sessions that translate model output into options, trade-offs, and a next step your leadership can sign off.
Rigorous methods, presented in terms your organisation can own
Acme clinic works with operations, product, and leadership teams that have data but lack a clear route from numbers to choices. We combine statistical rigour with careful communication, so every model comes with its assumptions, limits, and reasoning written down. The aim is analysis your colleagues can question, reuse, and defend long after the engagement ends.
Tell visitors what you do and why it matters, in one or two clear sentences.
Small, senior, and accountable for every deliverable
Lead Data Scientist
Designs modelling strategies and oversees validation for every engagement.
Machine Learning Engineer
Builds reproducible pipelines and deploys scoring jobs into existing systems.
Analytics Consultant
Translates findings into decision options and runs the stakeholder workshops.
Statistician
Plans experiments and checks that conclusions match what the data supports.
Feedback from teams after a data review or modelling project
“We finally understood why the forecast moved, and we could explain it to our board without a single slide of equations.”
Priya S.
Operations lead, regional logistics firm
“The first workshop cut through three months of debate by naming the one question that mattered.”
Marcus O.
Head of product, retail platform
“Clear documentation meant our analysts could pick the model up and keep improving it on their own.”
Helen V.
Analytics manager, public sector agency
“They were candid about what the data could not tell us, which made the recommendations easier to trust.”
Jonas K.
Finance director, membership organisation
Writing about analysis you can explain
How a sharp problem statement saves weeks of exploratory detours.
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What importance scores reveal, and what they do not prove about cause.
Practical steps for agreeing sample sizes and stopping rules in advance.
Begin with a scoped discovery, then choose the depth of support you need. enkernnke
Final fees are confirmed after the first conversation.
₹1,098
A focused call to define the question
Review of available data sources
A written summary of recommended next steps
₹2,699
Exploratory review and data quality report
One modelling approach validated against holdout data
Explainable results and a decision workshop
₹5,299
Regular model reviews and refreshes
Automated pipelines and monitoring
Priority access to the team for new questions
We work with structured tables, time series, and event logs. We can also review text or image data where it supports your decision.
Not at the start. We begin with exports or read-only samples and only discuss wider access once the scope is agreed.
Yes. Every deliverable includes documentation, reproducible code, and a short handover so your team can run and review it.
We follow the data handling terms agreed with your organisation and can work inside your environment when required.
Tell us the decision you are trying to make, and we will suggest how to start.