Reports look backwards
You see last month's sales and cash, but not next month's shortfall until it arrives.
AI Analytics & Forecasting
AI analytics services that tell you what happens next, and how sure we are
We build forecasts, risk alerts and plain-English data assistants on top of the systems you already use. Every forecast is tested on your own history before you rely on it, and every answer shows where the number came from.
- Backtested on your history
- Ranges, not single guesses
- Answers show their source
Engineering team in Jaipur, India. Working with businesses in the US, UK, Europe, UAE, Australia and India.
Your dashboards show what happened. Decisions need what happens next.
Forecasts live in spreadsheets
Someone updates them by hand, nobody knows how accurate they were last time, and the numbers rarely agree across teams.
Data sits in too many places
Sales in the CRM, stock in the ERP, payments in the bank, calls in the phone system, and no single view joins them.
Every question becomes a ticket
Managers wait days for an analyst to pull a number, so most questions never get asked.
AI analytics closes all four gaps: one data model, forecasts with a known error rate, early alerts, and answers in seconds.
AI analytics services, built around business questions
Sales and demand forecasting
How much will we sell, of what, where and when? Forecasts by product, region or channel, so you stock, staff and spend ahead of demand.
Cash-flow and revenue forecasting
Will we have enough cash in eight weeks? A rolling forecast from invoices, bills, payroll and bank data, with the risky weeks highlighted.
VyapaarSenseChurn and payment-risk prediction
Which customers are likely to leave or pay late? A risk score for each account, so your team calls the right people first.
Anomaly and fraud alerts
Is something unusual happening right now? Alerts when sales, costs, refunds, attendance or transactions move outside their normal range.
Conversational analytics
Ask "What were our top ten products in Dubai last quarter?" and get the answer, a chart and the source table, in seconds, with your access rules applied.
Ask your dataAI dashboards and automated reports
Dashboards that explain themselves: weekly summaries written in plain language, sent by email, Slack or WhatsApp.
Underneath every model: data pipelines, a cleaned data model and a warehouse that your BI tools can also use.
We test every forecast on your past before it predicts your future
A forecast is only useful if you know how often it is right. So we measure it before you use it.
- Backtesting on your own history. We hide recent months, let the model forecast them, and compare its forecast with what actually happened.
- Beat the simple baseline first. Every model is compared with a basic method, such as "same as last year" or a moving average. If AI does not beat it, we tell you and use the simpler method.
- Ranges, not single numbers. You get a likely range for each period, so you can plan for the low case as well as the expected one.
- Accuracy you can track. The error rate is shown on the dashboard and re-measured every month, and the model is retrained when it drifts.
Ask questions about your business in plain English
A conversational analytics assistant connects to your data model and answers questions from managers who will never write SQL.
- Read-only access to the data you approve, never write access
- Your existing permissions apply, so each person sees only their own region, team or clinic
- Every answer shows the source table and the query behind it
- If the data cannot answer the question, the assistant says so instead of guessing
Want an assistant that answers from documents instead of databases? Generative AI development
What changes when you add AI to your analytics
| Traditional BI dashboards | AI analytics from Prilient Our approach | |
|---|---|---|
| Main question answered | What happened? | What happens next, and why? |
| Forecasts | Spreadsheet, updated by hand | Automated, retrained, error rate shown |
| Finding problems | Someone has to spot them on a chart | Alerts when a number moves out of range |
| Getting an answer | Ask an analyst, wait days | Ask in plain English, answer in seconds |
| Explaining results | Charts only | Charts plus a written summary of what changed |
| Acting on it | Manual follow-up | Alerts to email, Slack or WhatsApp, or a hand-off to an AI agent |
You keep your BI tool. We add forecasting, alerts and a question-answering layer on top of it.
Works with the systems you already have
- Accounting and ERP
- CRM and sales
- E-commerce and POS
- Databases and warehouses
- BI tools
- Files and channels
Not on the list? If it has an API, a database or an export, we can usually connect it.
From scattered data to a forecast your team uses
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Question and data check
We agree the business question, the decision it feeds and how success is measured, then check what data you have and how much history.
You get: a data-readiness note and a go or no-go.
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Connect and clean
We build pipelines from your systems into one data model and fix gaps, duplicates and mismatched codes.
You get: a clean, documented data model.
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Model and backtest
We train forecasting or risk models, compare them with a simple baseline and backtest them on your history.
You get: an accuracy report you can read without a data science degree.
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Deliver where people work
Forecasts, alerts and the question-answering assistant go into your dashboards, email, Slack or WhatsApp.
You get: a working tool your team uses in the pilot.
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Monitor and retrain
We track accuracy every month, retrain when it drifts and add new questions as they come up.
You get: monthly accuracy reports and support.
Not sure which question to start with? Our AI consulting team ranks your use cases first.
We build analytics into our own products first
Our forecasting and data work runs inside software that businesses use every day.
Own product · AI business software
VyapaarSense
AI business management software for SMBs, with cash-flow forecasts, bank reconciliation and document AI built in alongside billing, GST, inventory, POS and payroll.
See VyapaarSense
Client project · Document AI
DataSwitch
An AI document extraction platform we built for a client. It turns invoices, statements and forms into structured data, which is often the missing input for a forecast.
See our document AI
Own product · AI agents
Prilient AI Agents
Six AI agents (Receptionist, Customer Support, WhatsApp Lead Generation, Appointment Setter, Debt Collection and HR Interview Screening) that log every conversation as data you can analyse, and can act on an alert, for example by calling an overdue account.
See Prilient AI AgentsAI analytics use cases we build most often
Retail and e-commerce
Demand by product and store
Forecast stock needs, cut stock-outs and overstock, and plan promotions.
Healthcare clinics
Appointment demand and no-shows
Predict busy days and likely no-shows, then send reminders through an AI agent.
AI for healthcare clinicsManufacturing and distribution
Orders and raw materials
Forecast orders, plan purchasing and flag unusual scrap or downtime.
Finance, lending and collections
Cash flow and payment risk
Predict late payments and rank accounts for the collections team or the AI debt collection agent.
Security and facility services
Staffing and attendance
Forecast guard demand by site and flag attendance and overtime anomalies.
Tainaat WorkforceOSSaaS and subscriptions
Churn and expansion
Score accounts by churn risk and spot the ones ready to upgrade.
Ways to start with AI analytics
Forecast check
For teams that want to know whether AI can beat their current forecast. We backtest a forecast on a sample of your history and report the result.
Analytics pilot
For one business question, end to end: data pipeline, model, dashboard or assistant, and a month of use by your team.
Priced after a scoping call.
Build and run
For a full analytics layer across teams, with monthly monitoring, retraining and new questions added.
Length: monthly
Need data and AI engineers inside your own team instead? Data and AI engineers inside your own team
Your data stays under your control
- We sign an NDA before we see any data
- Read-only connections wherever possible, with access limited to the tables a project needs
- Personal data is masked or removed before modelling when the question does not need it
- Your data is never used to train public AI models
Questions businesses ask about AI analytics
What are AI analytics services?
AI analytics services use machine learning and generative AI on your business data to forecast what will happen, flag unusual changes early and answer questions in plain English. They sit on top of the data and BI tools you already have, and add forecasts, risk scores, alerts and a question-answering assistant.
How is AI analytics different from a BI dashboard?
A BI dashboard shows what has already happened. AI analytics adds what is likely to happen next, why a number changed and which accounts or products need attention. It can also explain results in a written summary and answer questions without an analyst building a new report.
How much historical data do we need for forecasting?
It depends on the question. Sales and demand forecasts work best with at least one to two years of history, so seasonal patterns show up. Churn and risk models need enough past examples of the outcome, such as customers who left. In the first step we check your data and tell you honestly whether it is enough.
How accurate are AI forecasts?
Accuracy depends on your data and your market, so we measure it rather than promise it. We backtest every model on your own history, compare it with a simple baseline such as "same as last year" and show you the error rate before you rely on it. If AI does not beat the simpler method, we tell you.
Can managers ask questions about our data in plain English?
Yes. A conversational analytics assistant connects to your data model and answers questions like "Which customers have not ordered in 60 days?" with a number, a chart and the source. It uses read-only access, applies your existing permissions and says so when the data cannot answer a question.
Which systems can you connect to?
We connect to accounting and ERP systems, CRMs, e-commerce and POS platforms, databases, data warehouses and spreadsheets, and we can feed results into Power BI, Looker Studio or Metabase. If a system has an API, a database or an export, we can usually connect it.
How long does an AI analytics project take, and what does it cost?
A forecast check on one question takes a few weeks. A full pilot, from data pipeline to a tool your team uses, usually takes longer, depending on how many systems are involved and how clean the data is. We quote a fixed price for each stage before it starts.
Do you work with companies outside India?
Yes. Our engineering team is in Jaipur, India, and we work with businesses in the US, UK, Europe, the UAE, Australia and India. Workshops run on video calls in your time zone.
Find out what your data can forecast
Tell us the decision you want to make earlier, such as how much to order, hire or keep in cash. We will check your data and tell you whether a forecast can help.