01
Frontier & open models
GPT, Claude, Llama, Qwen, and DeepSeek — with per-workload routing.
Expertise
Generative & Agentic AI stack.
Deep engineering across agents, RAG, evaluation harnesses, and self-hosted foundation models.
Practice
Expertise
Delivery
Riyadh · London · Lahore
Model
Fixed-scope · Retainer
Timeline
6–16 weeks / phase
01 — What we do
Three pillars that carry the practice.
02
RAG & knowledge retrieval
Hybrid retrieval, reranking, and chunking tuned per document class.
03
Agent orchestration
LangGraph, custom state machines, and durable execution over queue infrastructure.
“
We ship this practice as a small, opinionated system — running infrastructure, evaluation harnesses, and the rituals that make leadership trust the numbers.
02 — Capabilities
What we build inside this practice.
Every engagement is scoped as a small system, not a slide deck. You get running infrastructure, documentation, and the metric-store hooks to measure it.
Scope an engagement01Model routing & cost optimization
02Retrieval-augmented generation
03Fine-tuning & LoRA adapters
04Evaluation harness design
05LangGraph / durable agents
06Tool-use & function calling
07Prompt registry & versioning
08Guardrails & red-teaming
Reference architecture
How the pieces move.
03 — In production
Numbers from the field.
40%
Token cost reduction
With per-workload model routing.
92%
Eval pass rate
On production-scoped agent test suites.
<1s
P95 retrieval latency
With hybrid BM25 + vector search.
Ready to scope this into your stack?
Book a working session with a lead architect.