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Flagship practice · AI · GenAI · Agentic
Generative & Agentic AI, built into your product.
Our primary model is long-term, overseas AI engagements. We design, build and run RAG platforms, agentic chat, MCP connectors and autonomous agents — from model choice to custom embeddings and production deployment.
What we deliver
Deep, hands-on AI capability across the full stack.
RAG & knowledge systems
- Document ingestion & chunking pipelines
- Vector databases — pgvector, Pinecone, Azure AI Search
- Hybrid & semantic retrieval
- Grounded answers with citations
- Evaluation & guardrails
Agentic AI & MCP
- Autonomous & multi-agent workflows
- Model Context Protocol (MCP) servers
- Custom tools & connectors
- Function calling & orchestration
- Human-in-the-loop approvals
Applied GenAI products
- Agentic chat platforms
- Content generation at scale
- Copilots embedded in your app
- Multilingual (incl. Arabic) support
- Azure OpenAI, Claude & open models
Why IVAM
AI partners who ship to production.
We don't stop at prototypes. Our teams take AI features from proof-of-concept to governed, monitored production — with evaluation, cost control and security baked in.
Real products live
OPAL, AIDEN and ATORA run in production today.
Model-agnostic
Azure OpenAI, Claude, Llama & open models — fit to the job.
Governed & safe
Guardrails, evals, PII handling and audit trails.
Long-term teams
A dedicated AI crew that grows with your roadmap.
Tools & stack
The stack we run in production.
Where we add value
Put AI where it moves the needle.
Knowledge assistants
RAG copilots over your docs, tickets and wikis that answer with citations.
Customer-facing agents
Agentic chat that books, troubleshoots and transacts — with guardrails.
Process automation
Agents that read, decide and act across your systems via MCP & connectors.
Content & insight
Summarization, classification and generation at scale, multilingual.
How we work
From proof-of-value to production AI.
Discover & scope
We map goals, constraints and success metrics, then propose the right team and engagement model.
Assemble the team
A matched, senior squad spins up in days — integrated into your tools, standups and workflows.
Build in the open
Short cycles, working software every sprint, transparent progress. QA, PM and program management included.
Run & scale
We operate and improve in production, and grow the team as your roadmap expands.
What AI models do you work with?
Azure OpenAI, Anthropic Claude, GPT-4o, Llama and open-source models — chosen per use case, cost and data-residency needs.
Can you build RAG and agentic systems on our own data?
Yes — secure ingestion, embeddings, vector search and grounded retrieval, plus agentic workflows and MCP connectors over your systems.
How do you handle AI safety and governance?
Every build includes guardrails, evaluation, PII handling, audit trails and human-in-the-loop approvals where needed.
How quickly can we see a working prototype?
Typically 2–4 weeks for a functional proof-of-value on your data, before committing to a production build.
Let's build together
Ready to put AI to work in your product?
Extend your team with a dedicated, result-driven AI crew — on a long-term engagement that scales with you.