Samta.ai is a data science consulting company and data science services company for enterprises. We deliver AI and data science solutions across machine learning services, predictive analytics and data science development, from the first assessment to models in production.
As a data science consulting company, we turn scattered enterprise data into models and decisions that teams can trust. Most enterprises buy data science in pieces: a strategy deck from one firm, a model from a freelancer, a dashboard from a vendor.
Samta.ai brings data science consulting, machine learning services and predictive analytics under one team, so the people who find the opportunity are the people who build and hand over the solution.
We work on Microsoft, Snowflake and Databricks platforms,
with delivery offices in Nagpur and Noida, India.
You see the data, the use case and the expected effort first.
Each model is documented in plain language for business and risk reviewers.
Code, documentation and monitoring steps stay with you.
Our artificial intelligence services and data science services cover the full range of data science consulting services. Our AI & Data Science Solutions connect these services into one plan, and clients usually start with one service, then expand as the first results prove their value.
We assess your data, shortlist the use cases with the best return and set a roadmap.
This is where most enterprises should start if they are unsure which data science services they need.
We build, train and validate machine learning models for forecasting, classification and risk scoring.
Each model comes with documentation, test results and a plan for handover to your team.
We use historical data to predict demand, customer churn, credit risk or equipment failure.
Predictions reach business teams as scores and alerts inside the tools they already use.
When you need data pipelines, feature engineering and model code built into your own systems, our data science development services deliver working software, not prototypes.
We focus on scalable, maintainable solutions that integrate with your existing infrastructure.
We design AI and data science solutions that connect data, models and decisions in one workflow, with outputs that risk and compliance teams can review.
Where you need wider strategy or governance support, we connect you to our enterprise AI consulting team.
Every data science consulting engagement ends with working assets your team owns:
a clear data foundation, tested machine learning models and the documentation to run them.
Identify where the data for each decision lives and who owns it.
Check completeness, quality and access before modelling starts.
Score opportunities by business value and feasibility.
Fix formats, duplicates and missing values.
Turn raw fields into the variables models learn from.
Record where each dataset and feature came from.
Choose methods for accuracy and explainability.
Build models on your data with tested settings.
Compare each model against a simple baseline.
Predict demand, risk, churn or equipment failure.
Push predictions into the tools business teams already use.
Flag when outputs need review.
Record purpose, data, limits and tests.
Limit who can see and change data.
Agree sign-off before production.
DSA operates as a structured, end-to-end process transforming raw enterprise data into actionable intelligence and operational models:
We gather data from sensors, databases, transaction systems and customer interactions, and confirm where each source comes from and who may use it.
Missing values, duplicates and inconsistent records are fixed so that the foundation of every analysis is reliable.
We look for patterns, trends and relationships in the data, and test whether the question you want answered can be answered with the data you have.
Our data science team builds predictive or prescriptive models with machine learning and statistical methods, chosen for accuracy and for how well they can be explained.
Models are tested on data they have not seen, checked for bias and stability, and reviewed against the business rules they must follow.
Results are turned into findings that business owners can act on, with the assumptions and limits stated clearly.
We help you put the insights into decisions and operations,plan how models will be monitored and maintained after launch.
These are the outcomes our data science services are designed to support. Results depend on your data, scope and adoption, so we agree how success will be measured during the assessment.
Scoped use cases and a clear data foundation shorten the route from a data science idea to a model in use.
Predictive analytics built on consistent, connected data helps business teams decide with more confidence.
Reusable pipelines and documented features reduce repeated manual preparation work across data science development.
Validated, explainable machine learning services give risk, compliance and business owners the evidence they need to act.
The people who scope your data science consulting project are the people who build it. Nothing is lost in handover between a consultant and a development team.
We document how each model reaches its outputs, so credit, clinical, public-sector and operations teams can question a prediction before they act on it.
Data privacy, access control and model approval are part of the plan from day one. For deeper security and compliance needs, see our AI security and compliance services.
Protecting personal data and meeting data regulations is part of the design. Trust depends on robust data governance from the first record.
As models become more complex, we balance accuracy with the ability to explain why a prediction was made.
As data volumes grow, data science solutions must keep working. We design pipelines and models to scale with your data.
Our data science solutions are built around the rules and risks of each sector, not a generic template.
Clear answers to common questions about how our data science consulting services work, what to expect and how to get started.
Data science consulting services help an organisation decide which data problems to solve, prepare its data, build and test models, and put the results into decisions. They usually include an assessment, model development, validation and handover.
Tell us your business goal and the data you have. We will reply with a scoped next step for your data science consulting project.
Discuss your goals
and constraints.
Clarify the data and
the technical scope.
Agree a sensible next step,
such as an architecture review.
Share a few details and our team will get back to you with a scoped next step.
