Generative AI, machine learning,
and computer vision —
built into products people actually use.

AI that ships,
not just demos

Schedule a consultation
14+  Years
150+  Projects
GenAI · ML · NLP 

Where AI projects
actually break

Most AI projects don't fail at the idea stage.
They fail after — when real data hits the model
and nobody planned for what comes next.

Your data isn't ready — and no one told you

Your data isn't ready — and no one told you

It's messy, scattered across systems, or missing labels entirely. That's where most projects quietly stall.

The proof of concept never became a product

The proof of concept never became a product

A slick demo is easy. A model that holds up on live inputs, at scale, under real load — that's the hard part most teams skip.

It shipped, then slowly stopped working

It shipped, then slowly stopped working

Models drift as the world changes. Without monitoring and retraining, accuracy fades and no one notices until it's a problem.

AI and ML services
we cover

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Generative AI & LLMs

LLM-powered assistants, RAG systems, and content generation built on your data.

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Conversational AI & NLP

Chatbots, enterprise search, and document processing that truly understand language.

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Predictive ML & Data

Forecasting, recommendations, and anomaly detection that turn your data into decisions.

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MLOps & Deployment

Pipelines, monitoring, and retraining that keep models working after launch.

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AI Integration & Consulting

Not sure where AI fits? We help you scope what's realistic and build it into your product.

From proof of concept
to production

No six-month bets on faith. We prove value early, then scale what works — so you're never funding a black box.

01 — Data & Discovery

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We start with your data, systems, and the problem worth solving. If the data isn't ready, we say so before anyone writes code.

02 — Proof of Concept

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A focused build to test one use case on real data. In a few weeks, you'll know if it's worth going further.

03 — Production Build

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Once value is proven, we build for real — integrations, scale, and the engineering that makes a model reliable.

04 — Monitor & Improve

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Models drift over time. We set up monitoring and retraining so accuracy holds long after launch.

Vilmate
Have a use case in mind? Let's pressure-test it.
Book a call

Platforms
& tools

LLM & GenAI
ML & Data
MLOps & Cloud
GPT-icon
GPT
Claude-icon
Claude
Llama-icon
Llama
LangChain-icon
LangChain
Hugging Face-icon
Hugging Face
Pinecone-icon
Pinecone
PyTorch-icon
PyTorch
TensorFlow-icon
TensorFlow
scikit-learn-icon
scikit-learn
pandas-icon
pandas
XGBoost-icon
XGBoost
NumPy-icon
NumPy
Docker-icon
Docker
Kubernetes-icon
Kubernetes
MLflow-icon
MLflow
AWS SageMaker-icon
AWS SageMaker
Azure ML-icon
Azure ML
Vertex AI-icon
Vertex AI

What we build
with AI

AI assistants & chatbots
AI assistants & chatbots

LLM-powered assistants that answer from your data, handle support, and actually understand follow-up questions.

Document intelligence
Document intelligence

Extract, classify, and summarize contracts, invoices, and forms — turning piles of paperwork into structured data.

Recommendation engines
Recommendation engines

Personalized product, content, and search results that adapt to how each user actually behaves.

Forecasting & prediction
Forecasting & prediction

Models that see demand, churn, or risk coming — so decisions get made on data, not gut feel.

Enterprise search
Enterprise search

Ask a question in plain language, get the right answer from thousands of internal documents.

Why Vilmate

Your Team, Not a Rotation
Speed Without Shortcuts
ISO-Certified Quality
Nearshore Advantage
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You work with the same developers start to finish. No handoffs, no "let me check with the team", no lost context mid-project.
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We move fast — but not at the expense of code quality or architecture. Fast and clean aren't mutually exclusive.
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Our processes are ISO-certified. That means structured code reviews, clear documentation, and predictable delivery.
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Based in Eastern Europe, we overlap with US and EU working hours. Real-time collaboration without the timezone headache.

Selected work

A few AI projects that made it past the demo and into production.

See all cases
Awarebee
#ai
#saas
#tech
#wordpress
USA

Awarebee

Monitor website changes with AI
Complex website monitoring technology packaged into a market-ready SaaS product. Branded from scratch, with flexible subscriptions and AI-powered tracking dashboards users can actually work with.
View case study
AI-Powered Video Ad Platform
#adtech
#ai
#nest.js
#node.js
#postgresql
#react
USA

AI-Powered Video Ad Platform

Insert virtual 3D objects into videos with AI
The client had the AI engine. We built the product around it: scalable architecture, an intuitive web interface, and a workflow that requires no additional filming.
View case study
Voicea
#ai
#saas
#android
#ios
#ruby
#vue.js
USA

Voicea

AI-powered voice collaboration platform for more productive meetings
Meeting insights captured, discussion intent surfaced, key takeaways made actionable. Built across mobile, web, and data to keep teams focused on what actually matters.
View case study

Questions clients ask
before they start

How much does an AI/ML project cost?
It depends on the scope — data readiness, model complexity, integrations, and how far you want to take it. A focused proof of concept is a much smaller commitment than a full production system. We scope it properly on a discovery call before quoting anything, so you're not signing up for a number pulled out of thin air.
How long before we see something working?
A proof of concept usually takes a few weeks. That's the point of starting there — you get something real to evaluate before committing to a full build. Production timelines depend on complexity and how clean your data is, and we'll give you an honest estimate once we've scoped the work.
What if our data isn't ready?
That's the most common starting point, honestly. Messy, scattered, or unlabeled data is normal — part of our job is getting it into shape before any modeling happens. If the data genuinely can't support what you're after, we'll tell you early rather than burn budget finding out later.
Do we need a huge dataset to start?
Not always. Some problems need a lot of labeled data; others can lean on pre-trained models and a smaller, well-prepared set. It depends on what you're solving. We'll assess what you have and tell you whether it's enough — or what it'd take to get there.
What happens after the model goes live?
Models drift as real-world data shifts, so launch isn't the finish line. We set up monitoring and retraining to keep accuracy from sliding over time. Some clients want us running that long-term; others prefer we hand it off with a setup their own team can manage.

Let's build AI
that ships

Whether you've got a use case in mind or just a problem worth solving — let's pressure-test it together and figure out what's real.
Prefer a call?
Pick a time that works for you.
Book a call




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