Custom AI Agents
Goal-oriented agents that take real actions inside your systems — not just chat windows.
AI Development Company in Qatar — Qatar
AI development in Qatar — custom agents, built to ship.
We build production AI systems for Qatari companies — custom agents, RAG pipelines, document Q&A, and bilingual copilots grounded in Anthropic Claude, OpenAI, and open-source LLMs. Real evaluation. Real safety. Real cost discipline. Not a ChatGPT wrapper with a logo on it.
Overview
Most AI projects in Doha don’t survive their first month in production.
We’ve seen the pattern across Qatar and the wider GCC: a flashy demo gets approved, an agency plugs in an OpenAI key, a chatbot appears on the website, and within weeks it’s hallucinating product details, quoting wrong prices, or refusing to answer in Arabic. The team quietly turns it off and adds “AI” to the back of the strategy deck.
Pixeldhow builds AI the way serious engineering teams build any other production system — with evaluations, observability, guardrails, retries, fallbacks, and cost budgets. Our work spans Anthropic Claude, OpenAI GPT-4o, and open-source models routed through a single, model-agnostic layer. The result is AI infrastructure that survives launch day, scales with usage, and gets cheaper over time as we tune it.
Arabic is treated as a first-class language, not an afterthought. We benchmark Gulf-Arabic retrieval, hallucination, and fluency on every project we ship. We pick the model that actually performs in Arabic for the task at hand — and we re-evaluate as new releases land, because the leaderboard changes every quarter.
Whether you need an internal RAG assistant that answers from ten thousand PDFs, a customer-facing agent that books appointments and pulls from your CRM, or a multi-agent system that handles entire workflows end-to-end — we scope it, design it, build it against an eval harness, ship it, and stay on to optimize it as the model landscape keeps shifting.
Deliverables
Everything you need. Nothing you don't.
Process
How we ship. Five steps, zero drama.
- STEP 011–2 weeks
Discovery
Workshop with your team to map the actual problem, the data available, the success metrics, and the constraints. We leave with a written brief, a measurable outcome, and a fixed proposal — not a vague hand-wave at AI.
- STEP 021–2 weeks
Design
Architecture decisions: model selection, RAG vs fine-tuning vs hybrid, retrieval strategy, vector store, eval plan, safety layer, and deployment target. Reviewed end-to-end before a single API call.
- STEP 034–10 weeks
Build
Iterative builds against an evaluation harness from day one. Every prompt change runs against a graded test set so we know we're getting better, not just different. Weekly demo + retro.
- STEP 041 week
Launch
Production hardening, rate limits, logging, observability, cost tracking, content moderation, fallback flows, and a final safety review before we route real users through it.
- STEP 05Ongoing
Optimize
Post-launch we monitor accuracy, latency, cost, and user feedback. We re-evaluate model choice quarterly, prune prompts, refresh retrieval indexes, and ship improvements as new models drop.
Tech Stack
What we build with. And why.
Anthropic ClaudeOpus, Sonnet, Haiku — primary reasoning models
Open-source LLMsLlama, Qwen, Mistral via Together AI and Replicate
LangChain & LangGraphAgent orchestration and multi-step workflows
PineconeManaged vector database for high-scale retrieval
Hugging FaceOpen model hosting and fine-tuning pipelines
Cloudflare Workers AIEdge inference for low-latency, low-cost tasks
OpenAIGPT-4o, o1, structured outputs, function calling
Vercel AI SDKStreaming, tool calling, edge-deployed AI routes
Supabase pgvectorVector search co-located with Postgres data
Weaviate / QdrantSelf-hosted vector stores for sensitive workloads
AWS BedrockEnterprise model access with VPC-scoped privacy
Upstash Redis + ResendRate limits, caching, transactional notifications
Our stack is continuously evolving. We select tools based on security, performance, and long-term maintainability for your specific project.
Why Pixeldhow
Why Doha's best teams choose us. And stay.
Production systems, not demos
Half the AI work in Doha is glorified ChatGPT wrappers that die in week one. We build evaluation harnesses, safety layers, retry logic, fallback models, and cost budgets — the boring infrastructure that turns a demo into a real product.
Model-agnostic by design
We're not married to one provider. Anthropic for nuanced reasoning, OpenAI for tool-use, open-source for cost or privacy. We pick what fits the job and route between them dynamically — and we re-evaluate every quarter as new models ship.
Bilingual by default
Arabic is a first-class language in everything we build. We test retrieval in Arabic, evaluate hallucinations in Arabic, handle RTL output, and pick models that actually perform on Gulf Arabic — not whichever one Anglophone benchmarks rank highest.
Direct founder access in Doha
You don't get a sales engineer hopping calls from London. You get the founder, in Doha, on Qatar business hours, who has actually shipped the kind of system you're asking for.
FAQ
Questions, answered.
Don't see what you're looking for? Email hello@pixeldhow.com — we reply within one business day.
READY TO START
Let's build the AI system your business will actually use.
Book a free 30-minute discovery call. We'll talk through the problem, the data, and whether AI is genuinely the right tool — or whether you need something simpler. No sales pressure, no obligation.