Data & Analytics
Inside the Black Box of AI: How Data Labeling and Annotation Really Work
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...
Full-stack AI & data firm
Welzin is a full-stack AI and data firm: data science, AI engineering, and the MLOps to keep it running. We move your numbers - revenue, risk, uptime, margin. Senior engineers, in production from day one.
Data Science & ML
Statistical and ML modeling that turns messy data into decisions.
AI Engineering
RAG, copilots, and autonomous agents, grounded with evaluation and guardrails.
MLOps & Ownership
The pipelines and monitoring to keep it running; we own the metric, end to end.
Real systems in production for real teams. We scope to the metric that matters, ship it,
and stay accountable to moving it - shoulder to shoulder with the people who own the result.
What we do
Five disciplines, one senior pod - from the first model to a system running in production.
View all servicesWe 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.
The outcomes every engagement is scoped to move - the numbers a senior pod signs up to own, from the first model to a system running in production.
See our workof clients come back for the next build
uptime across platforms we operate
median time to first measured result
A senior pod accountable for the outcome, no juniors, no hand-offs.
One senior pod, from the first metric conversation to a system in production you own.
Talk to a senior engineerA senior pod maps the metric, the data, and the constraints, then scopes the smallest build that moves the number.
We ship to production from day one - real pipelines, evaluated agents, grounded GenAI - with you in the loop throughout.
We run what we build, watch the metric we agreed to move, and hand over a system your team can own.
Products born out of client work - the upskilling program our engineers run, the founder toolkit we wished we had, the annotation studio behind our vision models, and the credit stack behind smarter lending.
Senior pods only
A senior pod owns your metric end to end - the people who scope the work are the people who ship it. No juniors, no hand-offs.
In production from day one
The work is running and observable from the first sprint, not demoed at the end. You watch it move before you commit further.
Accountable to the number
We scope to the metric you need to move - revenue, risk, uptime, margin - then stay on the hook for it, in writing.
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