AI Development CompanyBuild AI systems
that work.

Quellix Labs is a custom AI development company building artificial intelligence business solutions around real business workflows. We prove the first release quickly, deliver production systems in weekly cycles, and include clear governance, rigorous evaluation, and structured handoff.

AI systems built for client workflows, with clear review points.

Talk to an AI Engineer See What We Build

Artificial Intelligence Business Solutions from a Custom AI Development Company

We integrate and optimize production-grade AI around your tools, data, approval moments, operating limits, and adoption roadmap.

AI Agent Development Services

Agents built around client tools, approval moments, and multi-step business tasks.

  • Task execution: Agents that move work through clear steps instead of leaving everything inside a chat window.

  • Tool and system actions: Connections to CRMs, ticketing tools, databases, internal APIs, browsers, and operations systems.

  • Scoped for your workflow: Built around the client systems, approvals, and launch model agreed before development.

Enterprise AI Search & RAG Solutions

Search and ask questions across company knowledge with cited answers.

  • Company knowledge search: Plain-language search across approved documents, SOPs, wikis, drives, tickets, and knowledge bases.

  • Grounded answers: Responses backed by citations, snippets, and source links so users can verify the answer.

AI Document Processing & Data Extraction Services

Extract and validate data from business documents.

  • Field extraction: Names, dates, amounts, IDs, clauses, line items, obligations, and other structured fields.

  • Classification and routing: Document type detection, exception paths, duplicate checks, and review queues.

Predictive Analytics & Recommendation Systems

Forecast, score, rank, and recommend better business actions.

  • Forecasting: Demand, revenue, inventory, staffing, usage, capacity, and operational forecasts.

  • Scoring and ranking: Churn, risk, lead, conversion, anomaly, propensity, product, and content ranking models.

AI Adoption Consulting & Integration Services

AI consulting for integration strategy, LLM selection, ChatGPT and Gemini workflows, governance, costs, memory, and fallback paths.

  • AI workflow fit: We use AI only where it adds clear value. We avoid forcing AI into tasks that need simple, rules-based logic.

  • Cost and token control: We optimize prompts, cache responses, and route models dynamically. This ensures AI doesn't become an invisible cost center.

Included in every build

Built for Safe & Efficient AI Delivery

Control

Clear owners, approval points, fallback paths, and limits for actions that need oversight.

Visibility

Logs, evaluation checks, source trails, documentation, and handoff notes your team can inspect after launch.

Efficiency

Cost-aware routing, lean retrieval, practical model choices, and update paths that avoid waste.

Process

How We Work
Fast proof, weekly delivery.

A low-risk delivery rhythm for turning messy operations into useful AI systems: review the workflow, prove the first version quickly, then ship production releases in weekly cycles.

Phase 01

Review the workflow

Bring requirements if you have them. If not, we map the task, data sources, permissions, risks, approval points, and smallest useful AI fit.

Workflow Architecture Illustrative workflow
01. INGEST
Data Intake
DBs & APIs
CONNECTED
02
AI Guardrails
Strict Limits
STANDBY
03
Human Gate
Sign-Off
GATED
Map task inputs, data vaults, and system APIsSOURCES IDENTIFIED
Phase 02

Build the working POC

For qualified opportunities, we create a focused proof with a real interface and AI behavior so the team can see the workflow before committing to the production build.

Illustrative workflow study
Stress Test Rig
01. INJECTION
Prompt Injection
Adversarial override defense
DEFLECTED ✓
Citation Grounding
Multi-vault provenance check
GROUNDED ✓
Schema Boundary
Dirty input recovery
RECONCILED ✓
Candidate
v0.1
Evaluating v0.1
TESTING
Stress testing failure boundariesLATENCY: 220ms
Phase 03

Deliver by milestones

After feedback, we scope production around agreed outcomes, acceptance criteria, monthly targets, deployment, documentation, and team handoff.

Illustrative workflow study
Staged Canary Release
01. SANDBOX (5%)
01
Sandbox
5% Traffic
0.00% ERR
02
Dept Pilot
25% Traffic
STANDBY
03
Rollout
0% Traffic
GATED
Sandbox verified against error budgetGATE 1 PASS

See the system before committing to the build.

The first pass is practical: where AI should help, which data can be used, who can approve actions, and where the system must stop. When the direction is clear, production work moves through agreed milestones with architecture notes, evaluation checks, dashboards, and the limits your team needs before extending the system without us in the room.

Fast proof. Outcome-based builds.

Start with a free AI Fit Review. For qualified opportunities, we build a focused working POC before scoping production around delivery milestones and acceptance criteria.

Low RiskSee the workflow before committing to the production build.

Traditional Agency

  • How we start
    Paid discovery before proof
  • First proof
    Slides and estimates
  • Delivery rhythm
    Long timelines
  • Production pricing
    Hourly burn, unclear finish line

Quellix Labs

  • How we start
    Free AI Fit Review
  • First proof
    Working POC with real UI
  • Delivery rhythm
    Weekly build cycles
  • Production pricing
    Outcome milestones and acceptance criteria
See Pricing Details

Tell us where AI should help.

Consultations and project delivery are in English. You can submit your enquiry in the language of this page.

Email
contact@quellixlabs.com
Phone
+91 75684 93079
WhatsApp
Talk Through WhatsApp

What to send

Share the workflow you want to improve, the tools or data involved, the people who approve the work, and the outcome that would make the project worth doing.

What happens next

We review the context, identify whether AI should search, extract, score, draft, route, or stay out of the process, then suggest a practical first step.

Talk to an AI Engineer

Send name and email now. Add workflow context only if it helps us route the first reply.

No polished brief needed. One line, a tool name, or nothing at all is fine.

Make the Canadian review path explicit

For a Canadian organisation comparing custom development with a packaged tool, bring the workflow and the source systems a reviewer must inspect. Separate required capabilities from the parts a ready-made product already handles.

Quellix delivers from India and serves Canadian buyers remotely, including Toronto. Discuss permitted data access, the proposed hosting arrangement and reviewer availability in the project scope; Canadian data residency is not an automatic feature of remote delivery.

Can we set data-access requirements before sharing our Canadian business records?

Yes. Start by describing the workflow and constraints. Agree which representative or redacted samples are appropriate before transferring records, and settle access and deployment requirements before implementation.

Talk to an AI Engineer