LLM-backed features on your stack—chat, RAG, agents, and document AI.
We wire leading model APIs into your products: conversational UX, retrieval on your content, agentic workflows, and guarded production behavior—without pretending every problem needs a from-scratch model.
AI integrations add inference and tooling on top of systems you already run: websites, CRM, ops tools, and knowledge stores. You keep product ownership; we design prompts, retrieval, guardrails, and observability.
If training a custom model is warranted, that is a different program—we start from integration realism.
Most teams want leverage from LLMs without a research lab—integration is how that lands in a real product.
Useful framing before committing budget—most UAE-facing products start with APIs and retrieval.
| Criteria | Custom AI Build | AI API Integration |
|---|---|---|
| Time to Launch | Months to years | Weeks to months |
| Initial Cost | High—data, training, infrastructure | Lower—usage-based APIs |
| Maintenance | You own the model stack | Provider advances models; you own integration |
| Flexibility | Full control over architecture | Best-in-class models + your prompts and tools |
| Best For | Novel modeling, strict on-prem | Most product and ops use cases |
One grid—product surfaces and engineering depth together. Exact stack follows discovery and your risk profile.
Experiences & language
Chat & assistants
Rule-bound + LLM turns, context windows, and clean escalation to humans.
Multilingual & Arabic UX
RTL-friendly UI patterns and prompts tuned for mixed Arabic/English workflows.
Voice & media
Speech-to-text and text-to-spoken responses where voice fits the journey.
Knowledge & documents
RAG pipelines
Embeddings, vector stores, chunking strategy, and grounded answers with citations.
Knowledge ingestion
Index FAQs, SOPs, product catalogs, and tickets—without leaking private rows.
Document AI
Extract, classify, and summarize PDFs, forms, and contracts for downstream steps.
Agents & orchestration
Tool-calling agents
LLM steps that invoke your HTTP APIs, CRM actions, or booking flows—with allowlists.
Multi-step flows
Planning, memory limits, and recovery when a tool errors mid-run.
Multi-provider routing
Primary/fallback models or specialized small models for cheap classifiers.
Production & economics
Guardrails & evals
Golden sets on your content, regression checks when prompts or models change.
Resilience & limits
Timeouts, backoff, user-visible degradation, abuse controls at the edge.
Spend & latency visibility
Token accounting, caching where ethical, and alerts when cost or latency drifts.
We select models and hosts for latency, Arabic quality, cost, and residency—single or multi-provider setups for resilience.
Broad ecosystem, strong general reasoning, multimodal options for product teams moving fast.
Long-context conversations and careful defaults—good for heavy document review flows.
Pairs well with Google Cloud and Workspace estates; strong multilingual coverage.
Efficient options when throughput and unit economics dominate the decision.
Where Grok-class models fit your experimentation or research-heavy workflows.
Enterprise routes when contracts require regional hosting or unified cloud billing.
Model names move—we pin versions in architecture docs and regression tests, not only in marketing copy.
Concrete slices we scope in discovery—each maps to metrics you can inspect.
24/7 first-line answers, structured handoff to agents with full transcript and CRM payload.
Ask-your-docs against policies, playbooks, and SKUs—with refusal behavior when sources are thin.
Multi-step actions across APIs you already trust—booking, ticketing, enrichment—not open-ended autonomy.
Extract fields from invoices or forms, summarize packets, route by confidence thresholds.
Signals from conversations and behavior to prioritize queues—models augmenting your rules.
Draft variants and translation under glossary and tone guardrails—for marketing and ops.
Same model stack can power multiple touchpoints—permissions and data boundaries differ per channel.
Chat widget, semantic search, guided product Q&A.
Summaries, scoring assists, next-step suggestions tied to records.
Ops copilots, doc processing queues, workflow triggers.
Authoritative answers from uploaded or synced corpora—cited, not vibes.
Compliance and tone constraints change by sector—discovery captures them as non-negotiables.
Triage assistants, appointment FAQs, document summarization—never diagnostic claims without policy.
Listing Q&A, lead capture, RAG on brochures and inventory feeds.
Course Q&A, RAG on curriculum, accessible multilingual explanations.
Draft assist, clause extraction, research acceleration—always with human review.
Product Q&A, support bots, returns guidance, campaign copy variation.
Summarization, tagging, translation, adaptation across channels.
LLM features amplify data governance—design starts with what must never leave your boundary.
Our work is scoped as engineering; model usage is billed by the provider and should be budgeted explicitly.
Defined assistant or RAG slice with acceptance tests—ideal when corpus and channels are stable.
Exploration, eval iterations, or multi-agent expansion when the path shifts weekly.
Ongoing prompt/model updates, eval reruns, and cost guardrails after launch.
Rough timelines: narrow chatbots or single-corpus RAG often ship in weeks; multi-agent or heavily regulated flows commonly run longer—scoped after discovery.
Let's discuss how we can help bring your vision to life.
Sharjah, United Arab Emirates
Dubai, United Arab Emirates