Unibrix

#logo-full
#menu

 

#logo-full
#close
Start building now
#arrow-right
Get in touch
#envelope
LET'S BUILD

Ready to start your project?

Tell us about your challenge. We'll engineer a solution that scales with precision.

#envelope
EMAIL
contact@unibrix.io
#calendar
SCHEDULE
Book a 30-min consultation
We typically respond within 24 hours
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Close
Back to Services
#arrow-left

AI Development Services

[ LIVE ONLINE MUSIC LESSONS ]

Unibrix is an AI development services company that designs, builds, and integrates production-ready AI systems for startups and enterprises. We help companies build AI-ready product architecture, integrate LLMs and AI agents, and turn AI prototypes into scalable software.

ONLINE MUSIC-LEARNING MARKETPLACE
& LIVE LESSONS PLATFORM

Get Started
#arrow-right
Why it's different

Anyone can build an AI‍ demo. Production AI is different.

We don't bolt AI onto your product. We build it as part ofyour system, brick by brick.
Scalable infrastructure
AI system architecture
LLM integration
AI agents
ML development
Workflow automation
RAG & knowledge systems
Prompt engineering

Scale under real-world load

Integrate with existing software and APIs

Produce observable and controllable outputs

Protect sensitive data

Keep inference and infrastructure costs manageable

Support human oversight where necessary

Evolve as models and providers change

What we build

Nine ways we put AI to work

SaaS Integration
LLM & Agents
Agent Development
ML Software
AI Platforms
Architecture
RAG & Knowledge
Prompt Engineering
Scalable Infra

AI Integration for SaaS Products

We integrate AI into existing SaaS products without rebuilding everything around the model. The model stays a modular part of the architecture, not the architecture itself.

Clean AI integration, no chaos.

Recommendation engines

Intelligent search and discovery

Workflow automation

AI copilots and assistants

LLM-powered product features

Data enrichment pipelines

Classification and extraction

AI-powered analytics

LLM Integration & LLM Agents

We build software around large language models — OpenAI, Anthropic Claude, Gemini and others. The goal isn't just to connect an API, but to create a reliable LLM application architecture around it.

Reliable architecture, not just an API call.

LLM API integration

LLM agents

Multi-step AI workflows

Tool calling and function execution

Retrieval-augmented generation (RAG)

Structured outputs & model routing

Context and memory systems

Guardrails, validation & observability

AI Agent Development

Agents reason over context, use tools, retrieve information, and perform multi-step tasks. Architecture can include LangChain, LangGraph and DeepAgents, depending on the use case.

Clear permissions, context, tools, and boundaries.

Autonomous AI agents

Workflow agents

Sales and CRM agents

Research agents

Customer-support agents

Internal knowledge agents

Multi-agent workflows

Human-in-the-loop systems

Machine Learning Software Development

From models to production-ready systems — built for production performance, not experiments.

Built for production performance, not experiments.

Predictive analytics

Classification and scoring models

Fraud detection systems

Personalization engines

Recommendation systems

Anomaly detection

Data intelligence systems

AI Platform Development

For teams building AI-first products — custom platform development from architecture through production.

A modular foundation for long-term AI growth.

Custom AI platforms

AI-enabled SaaS products

Data pipelines and orchestration

Model lifecycle management

Vector databases & RAG infrastructure

AI APIs & model routing

Monitoring and observability

Secure execution environments

AI System Architecture Design

Before writing code, we design the system — separating business logic, data, AI models, and interfaces so components can evolve independently.

Architecture first. AI second.

AI-ready product architecture

Modular AI infrastructure for enterprise software

Decoupled model layers

AI service boundaries

Vector and knowledge layers

Model-provider abstraction & fallback mechanisms

Cost controls

RAG & AI Knowledge Bases

LLMs become far more useful with the right company or product knowledge. We connect language models with structured and unstructured data.

Give the model the right context — not just a longer prompt.

Retrieval-augmented generation (RAG)

Vector databases & semantic search

Document retrieval

Corporate knowledge assistants

GraphRAG

Permission-aware retrieval

Source attribution

Prompt Engineering & AI Evaluation

Production AI requires more than finding the right wording. For complex systems, we combine prompting with architecture, retrieval, guardrails and observability.

Prompts are part of the system — not the whole system.

System prompt design

Structured prompting & context engineering

Reusable prompt templates

Prompt versioning

Output validation

Evaluation datasets

Model comparison & regression testing

Scalable AI Infrastructure

AI is expensive. Bad architecture makes it worse. We build infrastructure that grows without turning every usage spike into an incident.

Control costs without limiting growth.

Optimize model and compute usage

Route requests between models

Scale on demand

Monitor latency and failures

Control token and inference costs

Support model switching

Remain observable

Vibe coding & AI-assisted development

From vibe-coded MVP to production software

Tools like Cursor, Claude Code, Codex, Gemini Code and OpenCode let teams turn prompts into working prototypes fast. That's useful, but a working prototype isn't automatically a maintainable product.
Get an AI codebase audit →
#arrow-right
Keep the speed. Add the architecture.

Vibe-coded app support & AI-generated code review

AI codebase audits

Architecture cleanup

Prompt and agent rules

Database and API guardrails

Security reviews & testing strategy

Documentation & human developer handoff

Production scaling

Industry-focused AI development

We build industry-specific AI software

Fintech

Fraud detection & risk scoring

Transaction monitoring

Financial workflow automation

AI-powered customer support

Document processing

Financial workflow automation

Intelligent product discovery

Secure, observable, built for real workflows

Healthcare

Healthcare data analysis

Workflow automation

Clinical decision-support systems

Intelligent data visualization

Patient-facing AI assistants

Healthcare knowledge systems

Predictive analytics

Privacy and security by design

Marketplaces

Recommendation engines

Personalized product discovery

Intelligent search

Dynamic ranking & supply-demandmatching seller and product classification

AI-assisted moderation

Pricing intelligence

Help users discover what matters instead of making them search for it.

Fashion

AI fashion recommendation engines

Outfit recommendations

Personalized clothing discovery

Visual product matching

Marketplace personalization

Intelligent search

User preference modeling

Product classification and tagging

Marketplace personalization

From browsing products to discovering the right products.

Education & EdTech

AI learning assistants

Adaptive learning systems

Personalized learning paths

AI tutors and copilots

Learning recommendation engines

Learner analytics

Content classification

Skills and competency matching

Automated feedback

Intelligent knowledge bases

AI that supports learning rather than adding another chatbot.
Built on real product & data experience

Scalable data architecture

Real-time analytics

Complex data visualization

AI-powered product workflows

Recommendation and personalization systems

Automated business processes

Cloud infrastructure

Decision-support tools

View case study Omniscience
Omniscience – Visualizing Big Data Algorithms
A scalable, cloud-ready data intelligence platform built around large datasets, analytics and complex algorithm visualization.
View case study
#arrow-right
View case study SnapNutrition
SnapNutrition
Combines multiple input modes with OpenAI/Anthropic-powered analysis, keeping the broader product workflow intentionally simple.
View case study
#arrow-right
Modern AI technology stack
LLMs & models
OpenAI · Anthropic Claude · Google Gemini
Agents & orchestration
LangChain · LangGraph · DeepAgents
Knowledge & retrieval
RAG · Vector Databases · GraphRAG
Observability
Langfuse · LangSmith
Secure AI execution
E2B · Daytona
Model routing & cost
OpenRouter
Agent integrations
MCP servers
Agent interfaces
AG-UI · A2UI
AI-assisted development
Cursor · Claude Code · Codex · Gemini Code · OpenCode

How We Build AI Products

AI Discovery

We identify where AI adds measurable value — and where traditional software is still the better solution.
01

Data & Architecture

We design the data flows, model layer, integrations, security boundaries and AI-ready product architecture.
02

Prototype & Evaluation

We test models, prompts, retrieval strategies and workflows before locking them into the product.
03

AI Integration

We integrate AI into the existing application, APIs and business processes.
04

Production & Scaling

We monitor quality, latency, reliability and cost — and improve the system using real usage data.
05
Why Unibrix
Dedicated Development Team
Long-term AI product development.
IT Staff Augmentation
Add AI and software engineering expertise to your existing team.
IT Outsourcing
Full-cycle AI software development.

FAQ

What AI development services does Unibrix provide?
Unibrix provides custom AI development services including LLM integration, AI agent development, machine learning systems, RAG and AI knowledge bases, recommendation engines, AI workflow automation, prompt engineering, AI platform development, and AI system architecture.
Can Unibrix integrate AI into an existing SaaS product?
Yes. We can introduce AI as a modular service layer connected to your existing APIs, data and business logic. This makes it easier to monitor, replace or scale individual models without tightly coupling them to the core application.
What is the difference between an LLM integration and an AI agent?
An LLM integration typically uses a large language model to perform a defined task such as summarization or classification. An AI agent can combine an LLM with tools, data, memory and business logic to plan and execute multi-step workflows.
In the case of a growing startup, a dedicated software team will save money and time on hiring employees and developing the product faster. Your specialists can deal with business-oriented tasks, and the development team will do additional work.

Another option is when you need help from dedicated development projects with unclear requirements. If you do not know precisely how to implement your idea, entrust your project to our professionals. This way, you can focus on the research stage without fear of overspending.

And for complex long-term projects, the Unibrix development team will help unlock the potential of your project and grow it. See our cases.
Does Unibrix provide prompt engineering services?
Yes. We use prompt engineering and context engineering as part of broader AI product development. This includes system prompts, structured outputs, prompt templates, versioning, evaluation and regression testing.
Can Unibrix work with a vibe-coded MVP?
Yes. If you have built an MVP using Cursor, Claude Code, Codex or similar AI coding tools, we can audit the codebase, identify architecture and security risks, establish engineering guardrails, and prepare the product for production.
What is RAG and when does an AI product need it?
Retrieval-augmented generation (RAG) allows an LLM to retrieve relevant information from a defined knowledge source before producing an answer. It is useful when an AI assistant needs access to company documents, product data, or domain-specific knowledge.
How do you make AI applications scalable and cost-efficient?
We treat models as independently managed services and design around caching, model routing, asynchronous processing, observability, token usage, fallbacks and appropriate model selection. The goal is to use expensive models where their capabilities matter rather than routing every task through the largest available model.
Which industries does Unibrix build AI solutions for?
Unibrix focuses particularly on fintech, healthcare, marketplaces, fashion, education/EdTech, SaaS and data-intensive products. Existing company work spans EdTech platforms, fashion personalization, analytics/data platforms and other modular software systems.
Can you build custom AI agents for our internal workflows?
Yes. We can build AI agents and workflow automation for internal use cases such as sales operations, research, knowledge retrieval, data enrichment, support and repetitive business processes. The agent can be integrated with existing software and APIs while maintaining defined permissions and human review points.
Do we need our own AI model?
Usually, no. Many products are better served by integrating existing foundation models and building proprietary value in the data, workflow, retrieval, business logic, evaluation and user experience around the model. Custom or specialized models make sense when the use case and economics justify them.

Final Thought

AI is not magic. It is another layer in your architecture. Vibe coding can build the first version. Prompt engineering can improve how the model behaves. LLMs can provide intelligence. AI agents can execute workflows. But architecture is what shapes those pieces into a product. If they don't fit, complexity grows. When they fit, AI becomes infrastructure.
Architecture first. AI second.
We design systems that can evolve independently, so business logic, data, models, and interfaces stay modular instead of brittle.
Production-ready from day one.
We build for scalability, observability, cost control, and reliability so AI becomes a trusted part of the product stack.

Tell us what you're building.

Whether it's an existing SaaS product, an AI agent, a new AI platform, or a vibe-coded MVP — we'll help you design the architecture and build it for production.
Book a Review
#arrow-right