News PwC India partners with Questt AI to deploy Intelligence Warehouse for enterprise AI Read the announcement →
Intelligence Warehouse

AI that decides the way your best people do.

Intelligence Warehouse holds how your company actually makes decisions, across functions, and puts that in front of every model and agent you run.

Talk to us See how it works
Customers includeZEE
0entities
0metrics
0decision rules
Entity Metric Decision
Capturing how the company decides…
PepsiCo Nokia Vodafone Unilever ArcelorMittal Adani Altius Zee Motherson AES Multiples
The problem

Same model. Same data. Different answer.

A category head asks

“Oral care share is down 1.2 points in Nielsen, but our billing is up 8%. What do we do?”

A model on your data

Sounds reasonable. Your category head would throw it out.
The same model on Intelligence Warehouse

Nielsen_Coverage_GapSame_Geo_DivergenceCompetitor_ActivityShare_Dilution
What your best category manager would have said.
How it works

BI needed a data warehouse. Enterprise AI needs an Intelligence Warehouse.

1Capture

Morrie interviews the people who make the call

MorrieNielsen says share is down. Billing is up. How do you reconcile that?
First, which geography and channel? Nielsen is thin in pharmacy. If it's urban GT, a competitor did something.
rule: Same_Geo_Divergence → Competitor_Activity (New_SKU OR Trade_Scheme)
2Structure

The warehouse stores it as a graph

Nielsen share Billing Pharmacy Competitor SKU rule Category vol. Sharedilution
Every node traces back to the session it came from
3Act

Your models and agents read from it

Recommendation
Counter-scheme in Urban South GT, week 2. Competitor ₹10 sachet. Not a sales loss.
Nielsen_Coverage_GapCompetitor_ActivityShare_Dilution
Use the model you already have
Decisions it handles

The same four kinds of decision show up in every industry.

decision circuit
96%decision accuracyFortune 100 telecom provider
34%fewer weather-driven stockoutsFortune 50 snacks & beverages company
Same daysignal to insight, from 3–4 weeksGlobal consumer healthcare company
6 wkskickoff to productionTypical first use case
Why it compounds

The first use case builds the warehouse. Every one after plugs into it.

Most AI projects start from zero each time. Here the second use case starts with the entities, metrics and rules the first one captured.

Use case 16 weeks · builds the base
Use case 211 days · <10% of the cost
Use case 3plugs into the same base
Fortune 100 telecom deployment
“For the first time, our sales team and supply chain team are working from the same reality. Decisions that used to take a week of cross-functional meetings now happen in minutes.”
VP of Operations, leading Indian FMCG company
Industries

Where it runs today

Consumer & Retail

Demand sensing, stock allocation, sales execution, integrated business planning.

OutletSKUDistributorClimate zoneScheme
34% fewer stockouts
Media & Entertainment

Subscriber conversion, churn, ad load per cohort, content ROI.

Viewer cohortTitlePaywall triggerPackAd slot
ZEE customer
Telecom & Infrastructure

Network modernisation, rollout sequencing, field operations.

SiteCrewEquipmentProgrammeRegion
96% decision accuracy
Team

Questt AI, Bengaluru

AS
Akhil Singh
Co-founder & CEO

Vision and go-to-market.

NP
Nidhi Prabhu
Co-founder & CPO

Product, and UX for complex enterprise workflows.

AT
Aniruddh Tammewar
AI & Technology

Core AI and graph infrastructure.

SG
Siddhartha Gupta
Chief of AI

Architecture of the intelligence layer.

AJ
Ankur Jain
Strategy & Operations

15+ years scaling portfolios from $2M to $38M.

Backed byCelesta CapitalChiratae VenturesPremji Invest

Start with one decision.

Pick the call your team argues about most. We'll have it running on your rules in six weeks.

akhil@questt.com nidhi@questt.com