Custom Data Applications · Built for Business

Your data is ready.
Your tools aren't.

DataVolt builds custom data applications that connect your databases, APIs, and files into one reliable process — with the calculation accuracy your business decisions depend on.

100%
calculation accuracy
1-click
results, always
10×
faster than manual
commission_calculator.app — DataVolt
Total Payout
₹8.4L
▲ 12% vs last
Agents
142
Processed ✓
Accuracy
100%
No errors
Monthly Commission Trend
Rajesh Kumar
₹42,500
Paid
Priya Sharma
₹38,200
Paid
Amit Verma
₹29,750
Pending
processed in
2.3 seconds
We connect to
MySQL / PostgreSQL REST APIs Excel / CSV Shopify Zoho CRM Google Sheets Tally Custom Sources
The Problem

Your data lives in
five different places.

Your CRM has the sales data. Your database has the transactions. Your finance team has the Excel. Your ops team has the CSV exports. And someone has to manually stitch it all together — every week, every month, every quarter.

The real risk isn't just the time lost. It's the calculation errors that slip through quietly, and the decisions made on numbers nobody can fully trust.

  • Data scattered across databases, APIs, files, and spreadsheets
  • Manual exports, copy-pastes, and formula-heavy Excel as the glue
  • Calculation errors in commissions, billing, or reconciliations
  • No single source of truth — every team has a different number
  • Processing takes days; decisions wait on the numbers
How it works today — without DataVolt
🗄️
CRM Database
MySQL export
🔌
Shopify API
Manual pull
📋
Finance Sheet
Excel / CSV
📧
Email Reports
Copy-paste
manual stitching every cycle
⚠️
commission_Q3_FINAL_v7.xlsx
1 person · 2 days · every month · error-prone
delayed, unreliable output
Wrong commissions
Billing disputes
Stale decisions
How It Works

Set it up once. Run it forever.

We translate your business rules and data sources into a reliable, repeatable application. No code needed from your end — ever.

1

We Map Your Process

We start by understanding where your data lives — databases, APIs, files, or a mix — and exactly what your business rules require. Every calculation, every edge case, documented.

DiscoveryData MappingRule Design
2

We Build the Application

We connect your data sources — live databases, third-party APIs, file uploads — and build an application that pulls, processes, and calculates with precision. One run, correct output.

API IntegrationsDB ConnectorsCustom Logic
3

You Run It. We Evolve It.

Your team operates the application independently. As your business rules change or new data sources are added, we update it. You scale, we keep pace.

HandoffTrainingOngoing Support
Use Cases

Complex calculations.
Any data source.

Whether your data lives in a database, a third-party API, an Excel file, or all three — DataVolt builds the application that processes it reliably.

💰

Commission Calculators

Multi-tier, role-based commission structures pulling live sales data from your CRM or database — calculated automatically, every period.

🤝

Revenue Sharing

Split revenues across partners, distributors, or agents with complex attribution logic connected directly to your transaction database.

🏷️

Pricing Calculators

Dynamic pricing engines with discount rules, volume tiers, and margin floors — fed from your product catalog API or database in real time.

📊

Usage-Based Billing

Pull usage data via API, apply your rate cards and thresholds, and generate reconciled billing outputs — without a single manual step.

🔄

Reconciliations

Connect to multiple data sources simultaneously — ERP, bank feeds, CRM — and match, flag, and resolve discrepancies automatically.

📈

Sales Schemes & Incentives

Complex slab-based, retroactive, SKU-level scheme calculations — whether the source is an Excel upload, Tally export, or a live database.

100%
Calculation accuracy — every run, every time. No more hunting for the one wrong formula that cascaded into 300 rows.
10×
Faster than manual Excel processing for large datasets
Rows — no crashes, no slowdown, no file size limits
Why DataVolt

One application.
All your sources. Zero errors.

  • 🔌
    Connects to Any Data Source
    Databases, REST APIs, Excel/CSV uploads, ERP exports — wherever your data actually lives.
  • 🎯
    Your Exact Business Logic
    Every tier, every exception, every edge case encoded precisely. Not a generic formula — your rules, built in.
  • 🔍
    Full Audit Trail
    Every calculation is logged with inputs and outputs. Always defensible — to auditors, partners, or your own finance team.
  • 💸
    Fixed-Scope, Fixed-Price
    No bloated SaaS subscriptions. Scoped engagements that deliver a working application — budget-friendly by design.
Case Studies

Built for real businesses.
Solving real problems.

From HR analytics to FMCG reconciliations — here's what DataVolt has delivered.

FMCG DistributionTransaction App

Transaction Classification System

A mid-size FMCG distributor needed to classify bank transactions across costs, payments, and sub-categories. Payments arrived via multiple UPIs — to the company, sales team, and receivables — making reconciliation complex and slow.

What we delivered

Automated classification — transactions intelligently categorised on upload, reducing manual effort
Multi-source payment handling — manages UPIs across company, sales, and receivables teams
Customisable categories — users can review and adjust classifications, ensuring accuracy
Auto
classification on upload
UPI sources reconciled
↓80%
manual effort
Astrology TechTraffic & Cohort

Traffic & Cohort Analysis

An astrology tech company needed visibility into sales orders, partial transactions, and the ROI of digital product marketing campaigns — with no reliable analytics infrastructure in place.

What we delivered

Traffic and cohort analysis across sales orders and partial transactions
Customer LTV and ROI evaluation across digital product marketing campaigns
Actionable insights to guide future campaign strategy and product decisions
LTV
measurement established
ROI
per campaign tracked
Social Media StartupRetention Strategy

User Retention Analysis & Strategy

A social media startup needed to understand why users were churning and what differentiated their retained users — to make targeted product and UX improvements.

What we delivered

In-product behaviour analysis to uncover differences between recurring and churned users
Drop-off point identification through data-driven cohort analysis
Actionable recommendations: UX improvements, feature nudges, onboarding enhancements
Churn
root causes identified
UX
improvements roadmapped
Handloom / RetailComputer Vision

Visual Fabric Similarity Search

A handloom fabric brand needed a way to find visually similar fabrics from a large swatch library — to help designers and brands discover replacements for out-of-stock items.

What we delivered

Computer vision model identifying close alternatives based on colour, texture, and weave
Swatch image library search — upload a sample, retrieve the closest matches instantly
Scalable image-matching pipeline deployable across the full product catalogue
CV
colour + texture matching
Auto
substitute discovery
Technology

Production-grade. Not prototype-grade.

We build on proven, enterprise-ready technology — not low-code tools that break at scale.

🐍
Python / Django
Backend logic & pipelines
🗄️
MySQL / PostgreSQL
Reliable data storage
🔌
REST API Integrations
Any third-party source
📊
D3.js / Charting
Interactive visualisations
Get Started

Tell us where your
data bottleneck is.

Whether it's a commission process in Excel, a billing workflow stitched across three APIs, or a reconciliation that costs your team two days every month — in 30 minutes, we'll show you exactly what a DataVolt application would look like.

No commitment. No sales deck. Just an honest conversation.

AI Readiness · For Growing Businesses

AI is only as good as
the data feeding it.

Most businesses aren't failing at AI because of the model. They're failing because their data is scattered, dirty, and unstructured. DataVolt fixes the foundation first — then helps you identify where AI actually creates value.

Your AI Readiness Journey
🗄️
Data Foundation
Clean pipelines · Structured storage
Complete ✓
🔌
Source Connectors
DB · APIs · Files unified
Complete ✓
🧭
AI Use Case Mapping
Identifying real opportunities
In Progress
🤖
AI Layer Integration
Models · Forecasting · Intelligence
Up Next
The AI Readiness Gap

Why most AI projects
fail before they start.

Businesses rush to buy AI tools or commission AI models — only to find that the output is unreliable, the results don't make sense, or the tool simply can't connect to their actual data.

The bottleneck is almost never the AI. It's always the data underneath it — fragmented, inconsistent, and not structured for machine consumption.

Before any AI can work reliably for your business, four things need to be true about your data.

📍
Centralized
All relevant data in one place — not split across ten exports and three team inboxes.
🧹
Clean
Consistent formats, no duplicates, no missing critical fields. AI trained on dirty data produces dirty predictions.
📐
Structured
Data modelled in a way that's machine-readable — not optimised for human eyeballs in Excel.
📅
Historical
Sufficient history to train, validate, and trust a model. Most SMBs discover they've never stored data systematically.
Our AI Readiness Framework

A structured path from data chaos to working AI.

We don't start with the AI layer. We start with the data layer — and work up. Every stage builds on the last.

1

Data Audit

Map every data source, assess quality, identify what's missing or unreliable.

Source inventory
Quality scoring
Gap identification
Readiness report
1–2 weeks
2

Data Foundation

Build clean pipelines, structured storage, and unified connectors across your sources.

Pipeline build
Source connectors
Structured DB schema
Historical backfill
3–6 weeks
3

AI Use Case Mapping

Identify which processes in your business are genuinely AI-ready — and which aren't yet.

Process analysis
ROI estimation
Prioritised roadmap
Honest no-go flags
1 week
4

AI Layer Build

Integrate the right AI layer — classification, forecasting, anomaly detection, or LLM — on top of clean data.

Model selection
Integration & testing
Team handoff
Monitoring setup
4–8 weeks
What AI Can Do For Your Business

Practical AI. Not science projects.

These are the AI applications that make real, measurable difference for mid-market businesses in India — grounded in the verticals we work with.

🧾

Smart Transaction Classification

Automatically classify bank transactions, invoices, or orders into cost categories, payment types, and sub-buckets — with human review only for exceptions.

FMCG · Finance · Distribution
📈

Demand Forecasting

Predict demand at SKU and channel level using your historical sales, seasonal patterns, and external signals — to optimise inventory and reduce stockouts.

D2C · FMCG · Retail
🚨

Anomaly Detection

Flag billing irregularities, reconciliation mismatches, or unusual sales patterns before they become disputes — in real time across your data pipeline.

Finance · Ops · Sales
💬

AI-Assisted Reporting

Ask questions about your data in plain language and get structured answers — no SQL, no pivot tables. Connect your warehouse to an LLM layer.

Leadership · Finance · Ops
📄

Document Intelligence

Extract structured data from unstructured sources — PDFs, invoices, contracts, delivery challans — and feed it directly into your data pipeline.

Procurement · Legal · Finance
🔮

Churn & Retention Prediction

Identify customers or users at high churn risk before they leave — based on behavioural patterns in your CRM, usage, and transaction data.

D2C · SaaS · Subscriptions
Our Commitment

We'll tell you when
you're not ready.

The AI consulting space is full of firms that will sell you a model before you have the data to support it. We won't. Our job is to help you get real ROI from AI — and that sometimes means telling you what not to do first.

Here's what we stand for:

🚫
We don't sell AI you don't need
If your process doesn't have sufficient data or clear ROI from AI, we'll tell you upfront — and suggest what to fix first instead.
🚫
We don't promise AI on broken data
Every AI engagement starts with a data audit. If the foundation isn't right, we fix that first — no exceptions.
We build for your scale, not enterprise scale
You don't need a data science team or a ₹50L budget. We scope AI projects to your actual size and deliver working results.
We hand it over and train your team
AI shouldn't be a black box. We document what we build, train your team to operate it, and make sure you're not dependent on us forever.
Free Assessment

Find out where you stand.
In 45 minutes.

Our AI Readiness Assessment is a structured conversation — not a sales pitch. We map your data, identify genuine AI opportunities, and tell you honestly what needs to be fixed first.

What you'll walk away with
A clear picture of your AI readiness — at no cost.
Data source inventory & quality assessment
2–3 specific AI opportunities for your business
Honest view of what needs fixing first
Rough effort & cost estimates to get started
No vendor lock-in recommendations
A written summary you can share internally

45-minute call · No commitment · Written summary included