AI development services that ship to production — not the demo folder.
AI chatbots, automation, machine learning, RAG and LLM integrations. Real systems with evals, guardrails, observability and cost controls.
AI development services cover the design, engineering and operation of AI-powered systems — including chatbots, automation, machine learning models, retrieval-augmented generation (RAG) and LLM integrations — built with evaluation, guardrails, observability and cost controls.
What we deliver with AI Development Services.
RAG-grounded chatbots for support, sales and internal teams.
Document, workflow and email automation with humans in the loop.
Forecasting, recommendations, fraud, vision — deployed to production.
Retrieval-augmented generation, done with evals and hybrid search.
GPT, Claude, Gemini and Llama integrated into your product.
Honest fit check.
A plain answer up front. We'd rather not sell you something you don't need.
- You want a chatbot grounded in your own docs and tickets
- You want LLMs inside an existing product with routing + cost control
- You want ML for forecasting, fraud, recommendations or churn
- You want repetitive ops work removed with AI automation
- You want 'an AI' with no concrete use case — book discovery first
- You need a hackathon demo tomorrow — we build systems, not prototypes
- You need guaranteed zero-error AI — accuracy is measured, not magical
Services in this area.
Our stack, battle-tested.
Which AI service do you need?
How we deliver.
Clarify goals, scope, constraints and the business metric this project must move.
Map flows, shape the information architecture and agree the technical approach before build starts.
Ship in short sprints with staging links, written decisions and weekly review checkpoints.
QA, accessibility, page performance, analytics and release planning are handled before launch day.
Post-launch support, measurement, iteration and handoff are planned from the start.
Starting from $700, depending on project scope and requirements. Model usage (OpenAI / Anthropic / cloud) is billed through your own accounts at cost — not marked up.
What makes us different.
The people you meet in discovery stay involved through architecture, delivery and launch.
Metadata, schema, page performance and semantic markup are part of delivery, not a post-launch add-on.
Tradeoffs, integrations and scope changes are documented so your team can audit decisions later.
Repos, infra, analytics and documentation live in your accounts from the beginning.
Compliance & regions
Data residency, language and timezone done deliberately — not retro-fitted.
Timezone overlap (ET + PT), SOC 2-aligned controls, HIPAA-ready engagements, USD billing.
GDPR-first delivery, EU data residency (AWS Frankfurt / Ireland), DPAs on request, EUR billing.
Arabic RTL UIs, UAE data residency, DIFC/ADGM awareness, KSA PDPL, AED/SAR billing.
Senior engineers, English-first delivery, global timezone coverage.
Frequently asked questions
Start with a scoped, measurable project — usually a chatbot on your docs or a document-extraction automation. Prove value in one workflow, then expand.
Yes — Llama 3, Mistral and others where privacy, cost or latency require it. We also use OpenAI, Anthropic and Gemini when they're the right tool.
Grounding with RAG, structured outputs, evals on a golden set, guardrails, source citations and human review where accuracy matters.
Cuibit AI development projects start from $700, depending on project scope and requirements. A scoped chatbot MVP, production RAG system and enterprise ML platform are each priced differently. Model usage (OpenAI, Anthropic, cloud) is billed at cost through your own accounts — never marked up.
Yes — we deploy with open-source models like Llama 3 and Mistral on your own infrastructure. Local vector databases (pgvector, Qdrant) keep all data on-premise. This is common for healthcare, legal and financial services clients.
RAG retrieves your documents at query time — best for knowledge that changes often. Fine-tuning trains the model on your data — best for consistent tone, format or specialised tasks. We often combine both for production chatbots.
We build a golden evaluation set before launch, run automated regression tests on every release, track per-answer quality scores, and set up human review loops for high-stakes workflows. Accuracy is measured, not assumed.
Related services.
Ready to start?
Tell us about your project. A senior strategist replies within one business day — with a written first take.