Assistants and RAG
Chat and search features that answer from your own documents and data, with citations back to the source so answers can be checked.
AI & agentic automation
AI features that do real work
GBixels adds AI to products: assistants that answer from your own documents, multi-step content generation pipelines, and agent workflows that automate manual work. We measure output quality against real examples before the feature reaches your users.
What you get
- Multi-agent workflows
- Content generation pipelines
- RAG & assistants
- Prompt engineering
What's included
What AI development covers.
LLM features that do real work: content pipelines, multi-agent workflows, assistants and retrieval over your own data.
Content generation pipelines
Multi-step pipelines that turn an input such as a topic or a document into finished output: text, images and audio, produced reliably at volume.
Multi-agent workflows
Workflows where separate steps plan, call your tools and check each other's output, used to automate work that used to be done by hand.
Evaluation and guardrails
A test set of real examples, scoring of output quality, cost and latency tracking, and fallbacks for when a model fails or returns something unusable.
What you receive
Every AI development engagement hands over working software and the material your team needs to run it.
- 01Working AI feature in your product
- 02Evaluation set and quality scores
- 03Prompt and pipeline source in your repo
- 04Cost and latency monitoring
- 05Fallback and retry handling
Related work
AI development we have shipped.
Live projects where we did this work. Open one to read how it was built.
GetXplain AI Platform
An AI-powered education platform that generates lessons, tutors students and gives educators learning analytics.
- Python
- FastAPI
- PostgreSQL
- SQLAlchemy
Qalam AI Mobile App
An AI writing assistant for Arabic and English that corrects grammar and generates content on your phone.
- Python
- AI/ML
- LLM APIs
- iOS
GetXplain Application
The desktop and mobile companion to GetXplain, bringing AI learning tools and lesson content offline.
- Flutter
- Python
- AI
- Cross-platform
What is RAG?
RAG stands for retrieval-augmented generation. Instead of relying on what a model memorised during training, the system first retrieves relevant passages from your own documents, then asks the model to answer using them. That keeps answers current and lets you show the source.
Which AI models do you use?
We are model-agnostic and pick per task based on output quality, latency and cost, then keep the integration swappable so you can move to a better or cheaper model later without a rewrite.
Can you add AI to an existing product?
Yes. Most AI work we do sits on top of a product that already exists. We start with one well-defined use case, measure whether it actually helps, and expand from there.
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Need this for your product?
Tell us where the project stands and what it has to do. We will come back with questions, a plan and an honest estimate.