Custom GPT Development Services
We build private, production-grade Custom GPTs and OpenAI Assistants for your operations, support and sales workflows — with retrieval augmented generation, real tool use, evals you can defend in a review, and human-in-the-loop wherever the stakes warrant it.
Beyond "ChatGPT With a Logo on It"
Most "Custom GPT" projects in 2026 are a system prompt pasted into the OpenAI Custom GPT builder, branded with a logo, and shipped with no plan for accuracy, no plan for evaluation, and no plan for what happens when the model is wrong. That works for an internal toy. It does not work when a customer-facing assistant gives a wrong policy answer, or when an internal ops copilot hallucinates a SKU that does not exist.
Our Custom GPT engagements treat the assistant as a piece of software, not a prompt. That means: retrieval augmented generation over your real knowledge base so the model answers from your data; tool use and function calling so the assistant can read live systems (your CRM, your order DB, your scheduling system) instead of guessing; evaluation harnesses with a ground-truth question set so accuracy is measured, not assumed; and human-in-the-loop review on every workflow where a wrong answer has a real cost.
We build on OpenAI's Assistants API (or Claude with tool use, depending on accuracy benchmarks against your workload) and host the orchestration on your infrastructure — Laravel, Next.js, or a managed orchestration platform — so your data does not leave a system you do not control. Data-residency for UAE and KSA clients is handled through OpenAI's enterprise data terms (data not used for training, region pinning where required) or via Azure OpenAI with EU-region hosting.
The deliverable is a Custom GPT plus the surrounding software that makes it reliable: the knowledge ingestion pipeline, the eval suite, the review dashboard, the observability that flags when accuracy drifts, and the documentation for your team to extend it. You can swap the underlying model, swap the vector DB, even swap us out, and the system still works.
The Five Custom GPT Use Cases That Pay Back Fast
Use cases we have shipped or scoped for UAE / GCC clients in the last 12 months. Each pays back in under 90 days at a typical SME scale.
Internal ops copilot
Answers staff questions from your SOPs, contracts, training PDFs. Cuts new-hire ramp time and stops senior staff from being a help-desk.
Customer service draft assistant
Drafts replies for your CS team in your brand voice with reference to order history. Human reviews and sends.
Sales SDR assistant
Qualifies inbound leads against your ICP, drafts personalised follow-ups, syncs to CRM.
Document intelligence
Extracts structured data from invoices, contracts, RFPs, passports. Posts drafts to your accounting / ERP for approval.
Product Q&A on storefronts
Answers buyer questions on ecommerce product pages from your spec sheet and policy docs. Increases conversion, reduces support tickets.
What's in Every Custom GPT Build
Same components, every engagement. The size of each grows with the use case.
Discovery + use-case definition
We sit with the operator (not just the manager) for 4-6 hours. Write what success looks like in measurable terms.
Knowledge ingestion pipeline
Documents chunked, embedded (text-embedding-3-large or Voyage), indexed in Pinecone, Weaviate, or pgvector on your Postgres.
Tool / function definitions
Functions the assistant can call against your live systems — read-only by default, write actions gated by human approval.
Evaluation harness
Ground-truth question set (50-200 Q/A pairs from your real ops). Automated regression tests on every model or prompt change.
Review dashboard
Where humans see assistant drafts, edit, approve, send. Built in the same Laravel/Next.js stack as the rest of your site.
Observability
Cost per session, latency P95, accuracy on eval set, user satisfaction signal. Shipped to Grafana or your existing analytics.
Documentation
Architecture diagram, runbook for prompt edits, runbook for adding new tools, hand-over recording.
Optional: human approval queue
When the use case demands it, every assistant reply lands in a queue for human review before sending.
Optional: voice surface
WhatsApp Business / Vapi / Retell front-end if voice is the right channel.
4-6 Week Engagement, From Brief to Production
No 6-month pilot that never ships. Production deployment is the explicit goal of week 6.
Discovery: shadow the operator, define ground truth, write SOW.
Prototype: knowledge base ingested, baseline assistant working against a 20-question eval set.
Tools: function calling against your real systems, read-only first.
Dashboard + human-in-the-loop: review queue, edit flow, send action.
Eval expansion (50-200 ground-truth Qs), accuracy tuning, observability shipped.
Production deploy + parallel A/B with the manual workflow. Measure time-saved and accuracy.
Models, Frameworks, and Why
| Layer | Default | When we deviate |
|---|---|---|
| Model | GPT-5 via OpenAI Assistants API | Claude 4 Sonnet/Opus when tool-use accuracy or long-context wins matter; Azure OpenAI for EU/UAE region pinning |
| Embeddings | text-embedding-3-large | Voyage 3 for cost-sensitive ingestion at scale |
| Vector store | pgvector on Postgres (Supabase or self-hosted) | Pinecone or Weaviate when collection exceeds 5M chunks or latency matters |
| Orchestration | Laravel jobs + queues; Next.js API routes for synchronous flows | LangGraph or custom workflow engine on complex multi-step agents |
| Eval | Custom harness with ground-truth Q/A in Postgres | Braintrust or LangSmith on larger deployments |
| Observability | Helicone or self-hosted Langfuse | OpenTelemetry to your existing Grafana stack |
| Front-end | Your existing site or a dedicated dashboard built in Next.js | Slack/Teams app surfaces when ops staff already live there |
Pricing
Custom GPT engagements start at AED 8,000 (~$2,180) for a single use case with limited tool integration. Production-grade multi-tool assistants with eval harness and human-in-the-loop typically land at AED 14,000-25,000. Recurring infrastructure cost after launch is normally AED 200-800/month depending on volume. Fixed-price terms apply.
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