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The Readiness Assessment

A 5-day engagement that maps your data, surfaces high-ROI AI candidates, and recommends a pilot — fixed price.

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Case study
Tier-1 bank cuts reconciliation 92%

Agentic reconciliation across 14 source systems — six-week pilot, full rollout in one quarter.

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New
Private AI on dedicated GPUs

Frontier-class models on isolated infrastructure — your data never leaves the perimeter.

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Latest
Field notes: agentic eval at production scale

How we ship and operate eval harnesses for systems running ten-million-plus actions a month.

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Founder
Rohit Wakode — Founder & Director

B.Tech IIT Bombay · LLB GLC Mumbai. Building intelligent enterprise systems in India since 2014.

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Industry · 04

Retail & E-commerce

Personalization that respects margin. Pricing that responds to the market in minutes. Conversational commerce that closes baskets without staffing chat.

PersonalizationPricingForecastingChat commerce

Retail AI only matters if it moves margin, not just clicks. We build personalisation, pricing, and conversational commerce tuned to your economics — and inventory intelligence so you sell what you have.

Everything is measured against real outcomes — basket size, sell-through, margin — not vanity engagement metrics.

SectorRetail, e-commerce, D2C, marketplaces
ScaleCatalogue- and traffic-scale ready
DeploysCloud or hybrid
Entry6-week pilot
01 — What we deploy

Personalisation that respects margin.

/ 01

Personalisation

Recommendations tuned to margin and inventory, not just affinity.

/ 02

Dynamic pricing

Market-responsive pricing within guardrails you set.

/ 03

Demand forecasting

SKU-level forecasts that cut both stockouts and markdowns.

/ 04

Conversational commerce

Assistants that close baskets without staffing live chat.

/ 05

Catalogue AI

Auto-enrichment, tagging, and search that finds the long tail.

/ 06

Returns & ops

Returns prediction and ops automation that protect margin.

02 — How we engage

From first call to production.

01

Discovery

02

Pilot

03

Production

04

Operate

STEP 01

Discovery

We pick the lever — personalisation, pricing, or forecasting — with the clearest margin impact.

STEP 02

Pilot

Built on your catalogue and transactions, measured against held-out performance.

STEP 03

Production

Integrated with commerce, OMS, and inventory; rolled out with guardrails.

STEP 04

Operate

Continuous measurement and tuning against margin, not clicks.

03 — Where it pays

Use cases.

PersonalizationPricingForecastingChat commerceCatalog AIReturns ops
04 — Engineering

Stack & standards.

Commerce
Commerce / OMS integration
Catalogue / PIM
Inventory
AI
Recommenders
Pricing models
Forecasting
Serving
Real-time inference
A/B measurement
Guardrails
05 — Outcomes

What good looks like.

Higher
Basket & margin
Personalisation tuned to economics.
Lower
Stockouts & markdowns
SKU-level forecasting.
Measured
On margin
Outcomes, not vanity metrics.
06 — Questions

Answers, before you ask.

Will personalisation hurt margin?
No — we optimise for margin and inventory, not just click affinity, with guardrails so recommendations never undercut your economics.
Can pricing stay within our rules?
Yes — dynamic pricing operates strictly within the floors, ceilings, and rules you define.
How do you prove impact?
Against held-out performance and live A/B tests measured on basket size, sell-through, and margin.
Ready when you are

Let's talk about Retail & E-commerce.

Start with a fixed-price 5-day Readiness Assessment or a 6-week pilot. Senior engineers, measurable evals, and a system you own on handover.

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