STACK AISOLUTIONSStack AI Solutions

Full-spectrum AI engineering

Engineering the next generation of AI products.

Agentic systems, generative AI, computer vision, ML, and NLP - designed, built, and deployed by our team. From prototype to production-grade, across every industry that takes AI seriously.

25+
AI products shipped
8+
Industries served
10+
Named clients

Describe a workflow. Watch an agent plan it.

The same plan → tools → outcome thinking we bring to every agentic build, running live against your problem.

> ask
> tap to run, or type your own
Agents
RAG
Tools
Memory
Eval
Guardrails

A live demo of how we scope agentic builds. Not a substitute for a discovery call.

Our own product

Stack Browser

Agents that work the web the way your team does - signing in to portals, filling forms, pulling data out of pages that have no API - with review checkpoints and a trail of every step they took.

See Stack Browser

stack browser · run

  1. download March invoices from the vendor portal
  2. opening portal.vendor.com … session restored
  3. navigating to Billing → Invoices
  4. filtering: March · 14 documents found
  5. downloading 14/14 … done
  6. complete - files delivered, run trail saved
Industries

Click an industry - see the work.

Eight industries, named clients, real production systems. Open any tile to see the case studies and engagements behind it.

Stories of impact

Real AI in production - with measurable outcomes.

01 / 04
Retail · BIBA01
GenAI
Synthesis

AI competitor-analysis product for BIBA

A GenAI system that monitors competitor pricing, assortment, and positioning across channels - turning multi-source data into merchandising decisions.

Multi-Source DataMerchandising Intel
Read case study
Healthcare · Theranow02
600
Sessions/Week

HIPAA-compliant telehealth platform

Encrypted video consultations, patient portals, and EHR integration - running real clinical sessions every month.

HIPAA CertifiedEHR Integrated
Read case study
Education · Khaitan03
Paper
Generation

Academic operations stack for Khaitan Education

Question-paper generation, PowerBI dashboards, and a unified data warehouse - turning fragmented academic data into one operational source of truth.

PowerBI DashboardsData Warehouse
Read case study
AgriTech · Kisanwala04
Farmer
Marketplace

Farmer platform & agri-data systems

AI-powered marketplace and operations platform for the agritech sector - connecting farmers, markets, and crop intelligence across fragmented networks.

Crop IntelligenceSupply-Chain Data
Read case study
The gaps you didn't know you had

Where AI can quietly cut your workload - by at least half.

Most teams have three or four spots in their week where AI can do half the work. These are the four we find most often - and there is a tool at the end of them for the ones we haven't listed.

Hours lost to manual data entry

Someone on your team is still typing data from PDFs, invoices, forms, and emails into spreadsheets and systems - every day, every week.

AI reads the documents, pulls the right fields, and routes them into the systems you already use. Your team only steps in when something genuinely needs a human call.

70% less manual entry · from Document-automation pipelines

Support answering the same questions every day

Whether it's customers or your own team - the same handful of questions get asked again and again, eating real hours from people who should be doing higher-value work.

An AI assistant trained on your knowledge handles the routine asks 24/7, and escalates the rest with the full context already attached for whoever picks it up.

~60% of tickets deflected · from Knowledge-grounded support assistants

Reports stitched together by hand each week

Every Friday or month-end, someone copy-pastes from spreadsheets, formats the charts, and writes the same kind of summary - for a meeting that's mostly looking at last week's number.

PowerBI / Fabric dashboards that update themselves, with AI-written summaries of what actually changed and what to look at first. The 'what to do about it' narrative comes free.

Hours → minutes · from PowerBI / Fabric reporting builds (e.g. Khaitan Education)

First drafts of routine content, written from scratch

Job descriptions, proposals, contracts, sales follow-ups, marketing copy - your team writes the same shapes of document over and over, starting from a blank page each time.

AI drafts the first version trained on your tone, your previous drafts, and your guardrails. Your people stop writing and start editing.

~80% off first-draft time · from Content-drafting assistants on client tone

Figures are representative outcomes from past engagements and will vary with your data, scope, and starting point.

Second opinion

None of these four? Describe your team and we'll look at yours.

Or start from
Entry points

Pick the path that fits you - we'll meet you there.

You have an AI idea. We get it to a working prototype in weeks.

You've got the use case and the buy-in - what you need is someone who's shipped this kind of thing before. We scope tightly, choose the right model and architecture, and put something working in your hands fast.

  1. Discovery workshop on the data, the metric, the constraints
  2. Architecture decision doc: model, infra, eval strategy
  3. Working prototype on real data, measured against your metric
  4. A roadmap to production with timelines you can defend

Your model works but won't scale. We harden it for real traffic and predictable cost.

It has to survive 10× the traffic, with audit trails, with costs you can forecast, and without waking anyone at 2 a.m. We turn fragile pilots into production systems.

  1. Performance and cost audit of the current deployment
  2. Observability and eval harness that catches regressions early
  3. Inference optimisation: caching, batching, routing
  4. Operational runbook and on-call patterns the team will use

You're adding AI to a product. We fit it to your stack without breaking the UX.

You don't need a new product - you need AI features inside the one you already ship. We integrate against your stack, respect the existing UX, and instrument the feature so you can prove ROI to the board.

  1. Stack and UX audit: where AI actually belongs
  2. Feature prototypes on your real data and constraints
  3. Phased rollout with flags, A/B, and success metrics
  4. Cost and latency budgets that match your economics

Your AI build is stuck. We find the real blocker and ship it.

The demo glowed. Then six months happened. We pick up stalled builds and get them across the line, diagnosing what is actually blocking rather than the symptoms, and fixing it in the order that ships.

  1. Honest diagnostic: model, system, or process
  2. A 30-day plan of the smallest moves that close the gap
  3. Eval, retrieval, deployment, or compliance work as needed
  4. Hand-off plan so your team owns it after we leave
Research & Development

What we're building for tomorrow.

Active R&D into the AI capabilities our clients will need next - wearable AI on Meta Glasses and Apple Vision Pro, edge inference, and multimodal agents.

Explore our research

Wearable AI

Building on Meta Glasses and Apple Vision Pro - ambient, on-device AI for spatial computing and always-on context.

Edge inference

Sub-50ms model serving on constrained hardware, quantized and distilled for the edge.

Multimodal agents

Agents that see, hear, and act across tools and modalities - beyond chat.

Trusted by teams shipping AI
Theranow
BIBA
Chiraharit
Khaitan Education
Andhra Prabha
Intalent
Acrodocz
The Grovel
Property Box
Humain Learning
Let's talk

Every project starts with a real conversation.

Share a few lines about what you're working on and we'll route it to the right person - usually within one business day.

We'll route it to the right person within one business day.