Custom AIBusiness IntelligenceMachine LearningEnterprise System Integration

Most AI projects don’t survive the pilot. Ours do.

A team of data scientists and AI engineers — 24 enterprise clients, 6 industries, Rs. 50Cr+ delivered in production. We build AI that ships. Not demos.

Trusted by enterprises across F&B, Manufacturing, Logistics, and Legal.

Capabilities

AI-first delivery. Enterprise-grade execution.

A practical execution model for moving AI from pilot to production, measured against an operational baseline.

Ships as workflow software

Custom AI Software

Build AI around live operating workflows, approvals, exceptions, and knowledge retrieval instead of isolated chatbot demos.

AI copilotsRAG systemsOperations apps
Creates one source of truth

BI & Decision Intelligence

Turn fragmented reporting into a trusted decision layer with shared metrics, executive visibility, and operational drill-downs.

Power BITableauMetric layers
Improves operational decisions

ML, Optimization & Automation

Forecast demand, allocate resources, route work, and automate decisions where manual planning cannot keep pace.

ForecastingInventoryRouting
Connects the stack

Enterprise Systems & Integration

Connect data, business systems, and automation into reliable production infrastructure your teams can operate.

SAPSalesforceData pipelines
Who We Work With

We build and deploy optimization solutions tailored to your scale.

Whether augmenting in-house data teams or acting as your dedicated decision science unit, we take your constraints and build models that run in production.

Enterprises

We build new AI and optimization systems alongside your teams, and improve the tools you already run from solver tuning to model rebuilds.

Best for teams with existing data, systems, and operational ownership.

Small & mid-size companies

We act as your decision science team, delivering production-grade AI and optimization capability that is hard to hire and staff in-house.

Best for teams that need senior delivery without building a full internal AI function.
Case Studies

AI for decisions. Not demonstrations.

What our systems actually do in production across enterprise supply chain, finance, customer experience, and legal operations.

01 / 07
DFM Foods (Crax) — Predictive SKU Recommendation & Boardroom Analytics
+15%
Distributor penetration increase in 90 days
FMCG & Snacks

DFM Foods (Crax) — Predictive SKU Recommendation & Boardroom Analytics

"Seven Billion helped us build and deploy an AI system in weeks that solved our key retail distribution bottlenecks."

Ankur Gupta
Ankur Gupta
Head IT, DFM Foods (Crax)
ECOSYSTEM & PARTNERS

Alliances and Partnerships

Seven Billion builds a robust ecosystem of top-tier AI and cloud platforms to amplify data-driven insights, delivering transformative value and empowering businesses to overcome obstacles with precision and agility.

FAQ

Straight answers to the questions that matter.

If it is not here, just ask.

Can't find your answer?

Book a call with the team 

Email us at hello@sevenbillion.co

How long does a typical engagement take?

Can your systems integrate with our existing infrastructure?

What does Phase 0 cost?

How do you measure ROI?

Do we need clean data before starting?

Will our internal team be involved?

How is our data kept secure?

What happens after deployment?

GOT QUESTIONS?

Questions we hear often.

If it is not here, just ask.

Can't find your answer?

Book a call with the team 

Email us at hello@sevenbillion.co

How long does a typical engagement take?

Can your systems integrate with our existing infrastructure?

What does Phase 0 cost?

How do you measure ROI?

Do we need clean data before starting?

Will our internal team be involved?

How is our data kept secure?

What happens after deployment?

GOT QUESTIONS?

Straight answers to the questions that matter.

If it is not here, just ask.

Can't find your answer?

Book a call with the team 

Email us at hello@sevenbillion.co

How long does a typical engagement take?

Can your systems integrate with our existing infrastructure?

What does Phase 0 cost?

How do you measure ROI?

Do we need clean data before starting?

Will our internal team be involved?

How is our data kept secure?

What happens after deployment?