Discover
We walk the line, the aisle, or the ward. We map the constraint, the data that exists, and the decision that has to change.
Sidstack Solutions Private Limited|Hyderabad
AI for the industries that make, move, and care.
We design and deploy production AI systems for manufacturing, retail, CPG, and health — grounded in real operations, throughput, and yield, not slides.
Shop-Floor Ready
Sub-15ms edge inference
Domain Copilots
Grounded in SOPs & MES
24/7 Operations
Unattended shift reliability
Edge Vision & TelemetryStatus: Nominal
Industries
Four domains. One way of working.
Plant, quality, and throughput•Practice
Manufacturing
AI that belongs on the shop floor.
Stores, stock, and the aisle•Practice
Retail
Decisions at the speed of the floor.
Brands, supply, and the shelf•Practice
CPG
From plant to pallet to panel.
Care, operations, and the record•Practice
Health
Assist the clinician. Never replace judgement.
What we build
Solutioning, not slideware.
Models are cheap. A system that a night-shift supervisor will trust is not. We take AI from a promising notebook to a running operation.
Explore solutions- 01
Operations intelligence
Live views of throughput, yield, labour, and exceptions — so supervisors act on the hour, not the month-end report.
- 02
Computer vision
Inspection, shelf, safety, and document vision models wired into the line, the store, and the clinic — not left in a notebook.
- 03
Forecasting and planning
Demand, inventory, and capacity models that respect promotions, seasonality, lead times, and the messy data you actually have.
- 04
Domain copilots
Assistants grounded in your SOPs, MES, ERP, and clinical notes. They draft, retrieve, and route. They do not invent policy.
- 05
Data platforms and MLOps
Pipelines, feature stores, evaluation, and model ops that survive shift changes, audits, and the next vendor swap.
- 06
Integration and change
SAP, Oracle, Dynamics, custom MES, EHR, and store systems. Training for the people who will run it on Monday morning.
How we work
Discover, design, deploy, distill.
A structured method to validate constraints before code and build systems that run unattended.
Design
Architecture before algorithms. Human workflow, model choice, integration path, and the metric that will prove it worked.
Deploy
Production systems with monitoring, fallbacks, and access control. If it cannot run unattended, it is not done.
Distill
Measure, retrain, and hand over. We leave operators with a system they own — not a dependency they cannot explain.
Selected work
Engagements, not case-study theatre.
Illustrative of the work we take on across high-mix production floors, omnichannel retail, and clinical wards.
Manufacturing
Vision inspection on a high-mix line
A discrete manufacturer needed defect catch-rate without slowing changeovers. We deployed in-line vision, tied rejects to root-cause codes, and put a live quality board on the cell.
Inspection in the cycle time, not after it.
Manufacturing practiceRetail
Store-level demand that buyers will use
A multi-banner retailer was over-ordering on fashion and stocked-out on basics. We built a demand model that planners could override, with a weekly ritual instead of a black box.
Forecasts that sit inside the buying meeting.
Retail practiceHealth
Documentation that gives clinicians time back
A hospital group was losing hours to notes. We designed a copilot grounded in local templates and coding rules — assistive, reviewed, and never a substitute for clinical judgement.
Drafts in the record. Decisions still with the clinician.
Health practice
The firm
Incorporated in Hyderabad. Built for the real economy.
Sidstack Solutions Private Limited was formed in 2022 to put AI to work where goods are made, sold, shipped, and care is delivered. We are a solutioning firm — not a lab, not a body shop.
- Founded
- 2022
- Home
- Hyderabad
- Focus
- Four industries
- Work
- Production AI
Start a conversation
Tell us about the operation you want to improve.
A plant, a banner, a brand, a pathway. We will tell you honestly whether AI is the right lever — and what it would take to put it in production.