Agents grounded in your data, not demos.
RAG systems, support and intake agents, voice agents, and automations that survive a Monday morning — with guardrails, handoffs, and honest limits.
Most AI demos die on contact with real customers. We build agents the unglamorous way: grounded in your actual data, tested against your actual edge cases, and designed to hand off to a human the moment they're out of depth.
What you get.
RAG over your private knowledge. Your services, prices, policies, and documents — retrieved, cited, and kept current.
Guardrails as standard. Prompt-injection defence, PII redaction, hallucination checks, and escalation triggers on every agent.
Human handoff built in. The agent knows what it doesn't know and routes to your team cleanly — transparent, never deceptive.
Bilingual by design. English + Arabic, tested with native speakers across Khaleeji, Egyptian, and Levantine dialects.
Channel-native deployment. WhatsApp Business, web chat, voice via Twilio, or inside your existing app.
Evaluation before launch. A test suite of real scenarios with pass thresholds — we ship when it passes, not when the demo looks good.
How this engagement runs.
Ground
1 weekKnowledge audit: what the agent must know, refuse, and escalate.
Architect
1 weekModel choice, retrieval design, guardrail layer, channel plan.
Build
2–5 weeksAgent + integrations, evaluated weekly against real scenarios.
Pilot
1–2 weeksShadow mode beside your team, then a controlled live slice.
Operate
OngoingMonitoring, eval regression runs, and monthly tuning.
Productized, AED-priced.
Spark
From AED 40,000
One agent, one channel — e.g. a website intake or FAQ agent with RAG.
Build
From AED 95,000
Multi-channel agent with booking/CRM integration and handoff.
Scale
From AED 200,000
Agent fleet or voice + chat with analytics and eval pipelines.
Custom
Let's scope it
Regulated-industry deployments and deep product integration.
Pricing reflects scope, not seniority. Every project gets senior engineers.
Questions buyers actually ask.
What's the difference between a chatbot and an agent?
A chatbot follows a script. An agent reasons over your data, takes actions — booking, qualifying, updating a CRM — and knows when to stop. We build agents; the script-following kind doesn't need us.
How do you prevent hallucinations?
Grounding plus refusal. Answers come from retrieved, cited content; when retrieval comes back empty, the agent says so and offers a human instead of improvising. We test this with adversarial questions before launch.
Where is our data stored?
In your accounts — your database, your vector store, your region. We default to UAE/GCC-compliant hosting and never train third-party models on your data.
Do you support Arabic?
Yes, properly. We test with native speakers across Khaleeji, Egyptian, and Levantine dialects — not just Modern Standard Arabic — because your customers don't write MSA.
What happens when the agent doesn't know?
It escalates within two messages — to your team's inbox, WhatsApp, or live chat — with the full conversation context attached. Customers consistently rate the honesty higher than a confident wrong answer.
Are you affiliated with OpenAI or Anthropic?
No. We're model-agnostic and pick per use case — Claude, GPT, or smaller open models when latency and cost argue for them. The architecture lets you switch providers without a rebuild.
Can you build voice agents?
Yes — phone agents via Twilio for booking, reminders, and triage, with the same grounding and handoff rules as chat.
Try the demo, then build your own.
Ask our live agent anything on the homepage — then book a call and we'll scope one grounded in your business.