01 / AI ENGINEERING
AI Product Engineering
A purpose-built experience that connects intelligence to the way your business works.
Designed for productionBRIVOX / AI ENGINEERINGAI DEVELOPMENT.
INTELLIGENCE CONNECTED TO REAL WORK.
AI DEVELOPMENT.
BUILT AROUND
YOUR BUSINESS.
Custom AI products, AI agents and automation connected to your company knowledge and software. Our engineering team operates from Egypt, with remote project collaboration available across Egypt, the Gulf and Europe.
Explore your AI opportunityOUR AI CAPABILITIES
SIX WAYS TO PUT
INTELLIGENCE TO WORK.
One engineering approach. Shaped around the problem you need to solve.
02 / AI ENGINEERING
AI Agents & Automation
Connect your tools and automate the steps between a request and a reviewed action.
Human approval where it matters
03 / AI ENGINEERING
Enterprise Knowledge & Search
Make company knowledge easier to find, with sources and access matched to each person.
Scoped access. Source-backed answers.
04 / AI ENGINEERING
Document Intelligence
Extract, classify and validate business information before it reaches your systems.
Traceable to the original document
05 / AI ENGINEERING
Predictive Intelligence
Build models around your data to investigate patterns and support better planning.
Evaluated against business baselines
06 / AI ENGINEERING
AI Infrastructure & Operations
Bring deployment, evaluation and operating visibility into the lifecycle of your AI systems.
Quality, visibility and cost controlWHAT THE WORK CAN LOOK LIKE
FROM A REQUEST.
TO A WORKFLOW.
Illustrative workflows, tailored to your data, policies and systems when we define the project.
A request becomes a reviewed action.
An agent gathers customer context, checks the business rules and prepares a quote. Your team approves the action before it reaches the next system.
Company knowledge becomes useful answers.
A colleague asks a question. The system retrieves relevant material within their permissions and returns an answer with sources they can inspect.
Documents become structured work.
An incoming document is classified, its fields are extracted and uncertain items are flagged for review before approved data enters the business workflow.
ENGINEERING THROUGH THE LIFECYCLE
USEFUL TODAY.
READY TO EVOLVE.
Quality, access and operating cost are part of the product.
A clear business task.
Define the workflow and the outcome before choosing a model. Start where intelligence can make the work more useful.
Controlled access & actions.
Apply the same roles and data boundaries as the business system. Give tools the permissions they need and keep important actions reviewable.
Evaluation with real examples.
Check quality against representative tasks and business baselines. Inspect failures and uncertainty before widening use.
Visibility throughout operation.
Track behavior, latency and cost. Plan fallbacks, incident handling and how changes to models or data will be evaluated.
AI should support a decision you can understand.
Outputs can be incomplete or wrong. We design around verification, appropriate human review and safe fallback behavior, especially where an action affects customers, money or access to information.
SCOPING YOUR AI PROJECT
A USEFUL TASK.
CLEAR DELIVERABLES.
Bring the workflow, a few real examples and the systems it must connect to.
We agree the users, data access, allowed actions and acceptance criteria before implementation. The scoped delivery can include a working application or integration, an evaluation set with documented results, and the deployment and operating instructions your team needs.
Data preparation, integrations, evaluation depth and release requirements shape the estimate. Model and infrastructure usage are operating costs and are discussed separately from the implementation quote.
Discuss an AI development projectQUESTIONS BEFORE A BUILD
PLAN THE
RIGHT FIRST STEP.
Can you connect AI agents to our existing software?
We review the available APIs, data ownership and permissions, then agree which actions an agent can propose or perform. Important actions can require human approval. Integrations and failure handling are part of the project scope.
What is needed for an AI knowledge search or RAG project?
Start with representative questions, the sources people should be allowed to use and the roles that can access them. We define retrieval, source citations and evaluation around those materials. Gaps in the source data need to be addressed before the system can give dependable answers.
What determines the cost and timeline of AI development?
The workflow, integration depth, data readiness, access controls and evaluation requirements determine the build scope. Model usage, retrieval, storage and monitoring also create operating costs. We separate the delivery quote from those ongoing costs and agree release milestones after scoping.
Can we begin with one AI workflow?
Yes. A first release can focus on a clearly bounded task, a representative test set and the permissions it needs. We agree what success and failure look like, how a person can review the output and what evidence is needed before expanding the workflow.
Read the engineering approach.
Building Permission-Aware Enterprise AI SearchRead the engineering approach.
AI Agent Development for Business: From Workflow to Safe ProductionRead the engineering approach.
Beyond the Prompt: Engineering Production-Ready AI Systems in 2026START WITH THE WORK YOU WANT TO IMPROVE.
YOUR BUSINESS.
A USEFUL AI SYSTEM.
A free meeting, prototype and demo. A clear direction for your business.
