Data strategy & assessment
A review of your data sources, quality and goals, ending in a practical roadmap that ranks data and AI use cases by return.
Overview
Data & AI built around your business.
AI is only as good as the data underneath it. Most businesses already have plenty of data, but it sits in spreadsheets, accounting software, CRMs and databases that do not agree with each other. KenStack’s data and AI services bring that data together, clean it and make it ready for reporting, analytics and machine learning.
We design data pipelines that pull from your existing systems on a schedule, model the data in a warehouse such as PostgreSQL, BigQuery or Snowflake, and add checks so missing or wrong values are caught before they reach a report. On top of that foundation we build BI dashboards for daily decisions and predictive models for demand, churn, pricing or risk.
Every model we put into production comes with MLOps: versioning, automated retraining, accuracy monitoring and cost tracking. You get one reliable source of truth for your business and AI that keeps performing as your data changes.
What We Build
Our data & ai services.
Data pipelines, warehouses and dashboards that make your data trustworthy, then AI and analytics on top of it.
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Data engineering & pipelines
Automated ETL and ELT pipelines that pull data from your CRM, ERP, apps and files on a schedule, with validation and alerts.
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Data warehouses & lakes
A central warehouse or lakehouse modelled around your business, so every team reports from the same numbers.
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BI dashboards & reporting
Interactive Power BI, Looker Studio or custom dashboards with the KPIs your managers check every day.
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Predictive analytics
Forecasting, scoring and anomaly detection models trained on your history to plan stock, staff and cash flow ahead.
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MLOps & model monitoring
Versioned models, automated retraining and accuracy, drift and cost monitoring for AI in production.
Why KenStack
Why choose KenStack for data & ai?
- One source of truth. Every report and model reads from the same cleaned, documented data.
- Faster decisions. Dashboards refresh automatically, so nobody waits for a monthly spreadsheet.
- AI-ready foundation. Data that is structured and governed for analytics and machine learning from day one.
- Governed and secure. Role-based access, audit logs and data kept in the region you choose.
Industries we serve
We have delivered data & ai projects for businesses across India and abroad, including:
How We Work
A clear, four-step delivery process.
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01
Discovery
A free call and short audit to understand goals, users, data and constraints, ending in a clear scope and quote.
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02
Design & architecture
Wireframes, data model and technical plan reviewed with you before development starts.
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03
Build in sprints
Development in one to two week sprints with a working demo and your feedback each time.
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04
Launch & support
Testing, deployment, training and a warranty period, then optional monthly support.
FAQ
Data & AI: common questions
What is the difference between data engineering and AI?
Data engineering collects, cleans and organises your data so it can be trusted. AI and analytics then use that data to predict, recommend or automate. Most AI projects fail on data quality, which is why we build both together.
Can you work with the tools we already use?
Yes. We connect to common databases, Tally and other accounting software, CRMs, ERPs, Google Sheets, Excel and APIs, and we can report in Power BI, Looker Studio or a custom dashboard.
Do we need a data warehouse to start?
Not always. For a single report or model we can start directly from your existing database. A warehouse becomes worthwhile when several systems and teams need the same numbers.
How long does a data and AI project take?
A first dashboard or data assessment usually takes 2 to 4 weeks. A warehouse with pipelines and predictive models typically takes 8 to 12 weeks, delivered in stages so you see value early.
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ExplorePlanning a data & ai project?
Tell us what you want to build. In a free 30-minute call we will suggest the right approach, scope and timeline, then send a fixed quote.