Full-stack AI & data firm
Welzin is a full-stack AI and data firm: data science, predictive analytics, AI engineering, MLOps/AIOps, and the product engineering to keep it running.
Startup or enterprise, we move your numbers - revenue, risk, uptime, margin. Senior engineers, in production from day one.
Data Science & ML
Predictive analytics, Data Engineering, Statistical and ML modeling that turns messy data into decisions.
AI Engineering
Generative AI and AI agent development - RAG, Tool use and Agents grounded with evaluation and guardrails.
MLOps & Operations
Scale on Kubernetes with DevOps/MLOps services that keep systems healthy in production: pipelines, drift monitoring & retraining.
Production systems for teams measured on the result. Each engagement starts with one metric; here is how far it moved once the system shipped.
3x
Organic reach
Client impact
Search is being rebuilt around answers, not links. CogNerd optimizes brands for ChatGPT, Gemini, Claude and Perplexity - keeping organic reach from quietly disappearing into AI answers.
6:1
Services vs software spend
Client impact
The world spends six dollars on services for every one on software. AI is finally coming for that larger number. A field guide to the full-stack AI firm, the shift from selling tools to owning outcomes, and why Welzin was built for it.
Read the case study92%
Calls resolved
Client impact
A national home-services brand was losing calls to hold times and after-hours gaps. Welzin shipped a production voice agent that answers naturally, books appointments, and writes back to the CRM - with guardrails and full observability.
Read the case study100%
Cash traceability
Client impact
A financial system of record for the field - where the cash is collected, the deliveries are made, and the money has always been hardest to see.
Read the case study31%
Fewer stockouts
Client impact
A national retailer was forecasting in spreadsheets and paying for it twice: stockouts on the fast movers, working capital buried in the slow ones. Welzin shipped a forecasting system that feeds replenishment directly - backtested, monitored, and owned to the metric.
Read the case study4x
Faster triage
Client impact
A retrieval-grounded copilot that drafts claim assessments with evaluation and guardrails, clearing the backlog without adding headcount.
Read the case study<50ms
Decision latency
Client impact
A streaming risk model scoring every transaction in flight, with drift monitoring that catches model decay before customers ever feel it.
Read the case study60%
Faster releases
Client impact
CI/CD for models, a feature store, and full observability, so a lean team ships and safely operates dozens of models in production.
Read the case studyWhat we do
Everything a production AI system needs - built, shipped, and operated by the same senior engineers.
We turn messy, real-world data into models and insight you can act on - rigorous, validated, and tied to a business question that matters.
Forecast demand, churn, risk, and revenue - wired into the decisions they drive.
Production GenAI and agents, grounded with evaluation and guardrails.
Pipelines, monitoring, and observability that catch drift before your users do.
APIs, apps, cloud, and data platforms - the product engineering around your AI.
What it looks like when a senior team stays accountable - shipped systems, returning clients, uptime, and speed to first result.
See our workproduction systems shipped and running
of clients return for the next build
uptime across platforms we operate
median time to first measured result
The team you meet on the first call is the team that ships.
From first conversation to a system you own in production - most clients see a measured result inside six weeks.
Talk to a senior engineerA senior engineer - not a salesperson - maps your metric, data, and constraints, then scopes the smallest build that can move the number.
We build in your environment and reach production early - evaluated pipelines, grounded GenAI, agents with guardrails - with you in the loop every week.
We operate what we shipped, report against the metric we agreed, and hand over a system your team can run without us.
A firm that ships products is a firm you can check up on - here's what we run ourselves, in production, under our own name.
Our product · Education
Ship-ready AI & data upskilling
Our product · Compliance & Finance
India startup compliance + the VC math
Our product · Fintech
Credit infrastructure for modern lenders
“Fraud losses fell 41% in the first quarter without adding review headcount. The engineers who scoped the model were the ones on call at launch.”
“Forecast error is down 32% across 1,400 SKUs, and their pod still reviews drift with us monthly. The first vendor that put the metric in the contract.”
“ETA accuracy went from 71% to 93% in eight weeks. No discovery theatre - a senior engineer was in our warehouse data by day three.”
“They rebuilt our inference stack before Series A diligence - serving costs down 47%, eval pass rates doubled, and the runbooks were ours from day one.”
Insights
What we’re learning building AI and data systems that hold up - written for the people who own the number, not the hype cycle.
Data & Analytics
Imagine a self-driving car merging onto a highway, recognising traffic lights and predicting where a cyclist is heading next. Or a warehouse robot weaving...
WOSS
In the rush to deploy AI agents across massive data landscapes, one silent killer lurks: missing context. AI models drown in raw metrics, CPU spikes, query...
GenAI & Agents
Large Language Models (LLMs) like GPT-4, LLaMA, and Claude now power critical real-world applications - from customer support bots that might accidentally...
Engineering
In this article, we’ll guide you step by step to build your very first React project using Lovable AI, connect it to Supabase, and publish it online. By the...
GenAI & Agents
Like explaining a project to a friend, you give background not 200 pages of docs. AI models face the same challenge with context length.
We are a full-stack AI & data firm across five disciplines: data science, predictive analytics, AI engineering (RAG, copilots, agents), MLOps/AIOps, and the product engineering that ships it all. One senior team owns the path from the first model to a system running in production - not slideware.
Anything where data should be driving a decision and is not yet: forecasting, risk and fraud scoring, churn, document and workflow automation, copilots and agents, and the data platforms underneath them. If it touches a number you care about, it is in scope.
A metric that’s stuck, a system that needs rescuing, or a build you want scoped - a senior engineer reads every note.
Talk to a senior engineer
