Infiteq
AI Integration

AI Features
That Actually Ship.
Not Demos.

Senior engineers embedding production-grade AI into your product — LLMs, OpenAI, Claude, RAG, vector search and embeddings, wired to your stack with evaluation, guardrails and real latency budgets.

What we build

AI Integrations, End to End

From first prompt to production traffic — grounded in your data, measured against real metrics, and built to scale.

LLM-Powered Features (GPT-4, Claude)

Summaries, drafting, classification, extraction and reasoning features powered by OpenAI GPT-4 and Anthropic Claude — wired into your product with streaming, caching and graceful fallbacks.

Retrieval-Augmented Generation (RAG)

Ground LLMs in your own documents, databases and knowledge base. We build end-to-end RAG pipelines with pgvector, Pinecone or Weaviate and measurable answer quality.

Custom AI Agents & Workflows

Tool-using agents that read your APIs, trigger actions and run multi-step workflows — built on function calling with full audit trails, guardrails and human-in-the-loop controls.

AI Chatbots & Copilots

In-app copilots and customer-facing chatbots that actually understand your product. Grounded in your data, evaluated against real conversations and deployable to web, Slack or mobile.

Vector Search & Embeddings

Semantic search over millions of records using OpenAI, Voyage or open-source embeddings. We tune chunking, hybrid ranking and filters so results stay fast and relevant at scale.

Fine-Tuning & Evaluation

Fine-tuned OpenAI models, LoRA adapters on open-source LLMs and rigorous evaluation harnesses. We benchmark accuracy, latency and cost before anything touches production.

How we Work

From Brief to Launch — Without the Wait

01

Discovery

We dive deep into your goals, users, and constraints.

02

Architecture

Senior engineers design a scalable, future-proof system.

03

AI-Accelerated Build

We code fast with AI tools — reviewed by seniors every step.

04

QA & Launch

Automated tests, manual review, zero-defect deployment.

05

Scale & Iterate

We stay on board to help your product grow.

Our Tech Stack

Built With the Best Tools Available

Let's build something

Your next product will be
faster.

Stop waiting months for results. We ship production-ready software in weeks — with senior engineers and AI at full speed.

Tell Us Your Idea
FAQ

AI Integration, Answered

Most products do not need a rewrite to adopt AI. Infiteq audits your stack, identifies 2–3 high-leverage use cases (search, support, drafting, classification) and ships the first one in 3–6 weeks behind a feature flag. We integrate with your existing APIs, auth and database, so AI feels like a native part of the product, not a bolted-on widget.

Hosted models like OpenAI GPT-4 and Anthropic Claude give you state-of-the-art reasoning in days, with no training data required. A custom or fine-tuned model only makes sense when you have a narrow, repeatable task, strict latency or cost targets, or data you cannot send to a third party. For 80% of product use cases, GPT-4 or Claude plus RAG beats a custom model on quality, cost and time-to-market.

We ground models in your data using RAG over a vector database (pgvector or Pinecone), constrain outputs with structured schemas and function calling, and run every release through an evaluation harness of labelled examples. Low-confidence answers are routed to a human or marked as "not sure" instead of guessing. Hallucination rate is tracked as a first-class production metric, not an afterthought.

RAG — Retrieval-Augmented Generation — is the pattern of retrieving relevant chunks from your own data and giving them to an LLM as context before it answers. Use RAG whenever the model needs knowledge it was not trained on: your docs, your product data, your customers or anything that changes. It is almost always the right first move before fine-tuning, because it is cheaper, easier to update and far more accurate.

We default to providers with zero-retention terms (OpenAI enterprise, Anthropic Claude via API) and can deploy on Azure OpenAI, AWS Bedrock or fully self-hosted open-source models (Llama, Mistral) where compliance demands it. PII is redacted at the boundary, prompts and outputs are logged with access controls, and every integration ships with a documented data flow. We have shipped AI into regulated environments with zero data leaks.

Reach Out To Us

We'd love to Hear From You.

Choose the way that works best for you — we're here to help.

Email Support

Our team can respond in real time.

office@infiteq.io
Phone Call

Available during working hours.

+381 64 9543 183
Book a Call

Available during working hours.

Our Location

Serbia-based, serving clients worldwide.

Belgrade, Serbia