Service · 07 of 08 — AI / ML Solutions

Decisions without
the intelligence to back them.

Two kinds of AI work. The kind where you call an API and get a response. The kind where you train a model on your specific data, build a prediction pipeline, and make your operations measurably smarter over time. Kyrex does both — and knows which one your problem actually needs.

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Kyrex AI Advisorgpt-4o-mini

Kyrex AI Advisor · Answers scoped to Kyrex services only

Trained, deployed, in production

Across active deployments · 2026

Custom ML model live

OneAtta — predictive analysis pipeline

RAG deployments

AskKubeir, MI-Way, Planet Genesis

Disciplines wired

From RAG to AI-powered decisioning

Knowledge chunks indexed

Across the AskKubeir RAG alone

What we build · 6 layers

Six layers.
Trained on your data.

AI/ML engineering across the whole stack — custom models, RAG knowledge, vector search, prediction pipelines, fine-tuned LLMs, decisioning. Built on your domain, never a wrapper around a generic API.

L01

Custom ML model development

Models trained on your data — not generic pre-trained models applied without context. Nutritional prediction, demand forecasting, classification, scoring.

L02

RAG knowledge systems

Retrieval-Augmented Generation — AI responses grounded in your specific knowledge base, not general training data. Precise, current, and yours.

L03

Vector embeddings and semantic search

Content embedded into vector databases — enabling semantic search, similarity matching, and intelligent retrieval at scale.

L04

Prediction pipelines

End-to-end: data input → model inference → structured output → operational action. Built for production, not a notebook.

L05

Fine-tuned LLM deployments

Large language models adapted to your domain — tone, knowledge, constraints, and behaviour defined for your use case.

L06

AI-powered decisioning

Models integrated into operational decision points — pricing, routing, allocation, recommendations — replacing manual judgement with learned intelligence.

Bridge → Engagement

Train it on what only you know.

All 6layers — domain-specific intelligence built on your data, not bolted onto someone else's API.

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In production · 2 systems live

Two categories.
Both in production.

A custom ML model trained on labelled food data. Three RAG knowledge bases serving immigration and e-commerce domains. Each grounded in a client's specific information, each running live.

CASE 01Production

Live

Custom ML model

OneAtta

Predictive analysis model trained on nutritional databases, manually labelled grain compositions, lab results, and food research data. Analyses blend compositions across taste, texture, health factors, allergens, and nutritional profile. Deployed in a production mobile application serving real users.

Trained on labelled grain compositions + lab results + food research
Predicts taste, texture, allergens, nutritional profile
Live in OneAtta — production mobile, real users

View case study

CASE 02Production

Live

Multi-tenant RAG

AskKubeir · MI-Way · Planet Genesis

Three separate RAG deployments — each trained on a different knowledge domain (immigration law, immigration consulting, jewellery e-commerce), each auto-syncing with new content, each delivering precise responses grounded in the client's specific information.

3 independent knowledge domains, 3 separate vector stores
Auto-sync pipelines on each — knowledge base stays current
Responses grounded in client content, not general training data

View case study

How we approach this

General models.
Specific decisions.

The most common AI mistake is using a general model where a specific one is needed. A general model knows everything about the world and nothing specific about your business.

Kyrex builds AI systems trained on specific data — your products, your domain, your operational context. The result is an AI layer that compounds value over time as more data flows through it, rather than a wrapper around a generic API call.

Two categories of AI work Kyrex delivers

RAG systems — knowledge bases that stay current, grounded in your content, precise in their responses
Custom ML models — trained on domain-specific data, deployed in production pipelines, making real decisions

Fit check

Honest about who
this is for.

Right fit · 6

Businesses with product or operational data that isn't being used analytically
Platforms making automated routing or assignment decisions that could be smarter
Products where personalisation would improve conversion or engagement
Operations where classification, scoring, or recommendation logic is being done manually
Any business where 'it depends' is the answer to a question a model could answer
Teams spending time on analysis that should be automated

Wrong fit · 5

You don't have operational data — machine learning requires a training history; without data, there's nothing to build a model on
You want AI because it sounds impressive — if a rule-based system or a lookup table solves the problem cleanly, we'll say so
You haven't defined what decision you're trying to automate — vague briefs produce models that answer the wrong question precisely
You need a generic chatbot wrapper around GPT — that's available off the shelf; we build when domain-specific intelligence is what's needed
You need a result in the next two weeks — data preparation, training, evaluation, and production deployment can't be compressed without sacrificing accuracy

Other disciplines

Portals & Custom Platforms

API & Integrations

DevOps & Reliability

AI / ML Solutions · Engagement options

Need AI in production?
Make sure you actually need it.

Most clients arrive thinking they need ML. Some actually need a rule-based system or a lookup table. The Blueprint tells you which — independent research, ₹15k credited if you proceed.

Path 01 · Start a project

If you have the data, the decision, and a clear use case.

Start a project.

Brief us on what you need built. We come back within one business day with scope, timeline, and cost.

Start a project

Path 02 · The BlueprintRecommended

If you're not sure whether ML, RAG, or a sharper rule is the right answer.

Get the Blueprint.

A fixed-fee engagement. We map your decision points, evaluate ML vs RAG vs rules, and hand you a written report covering every realistic path — yours to keep, with us or without.

₹15,000· credited if you proceed

Get the Blueprint

[email protected]Reply within 1 business day