Agents, voice AI, WhatsApp automation, RAG pipelines, MCP integrations, vibe-to-production hardening. We take ownership of the system after delivery. If it breaks at 3am, that is our problem too.
Eight production patterns. Each one shipped on a real customer, not a demo. Mix and match — most engagements pull from two or three.
You built it fast with Lovable, Cursor, Bolt, or v0. It works on your laptop. We take the prototype and harden it for the real world — auth, RLS, error handling, rate limiting, secrets management, CI/CD, monitoring. The natural follow-on to a Quick Scan.
Custom AI agents for internal ops and customer-facing workflows. LangGraph, CrewAI, and custom orchestration. Tool use, memory, and multi-agent pipelines. Built with the security review baked in — not added after.
Inbound and outbound voice agents for customer service, booking, and ops. Hospitality front desk automation, real estate inquiry handling, SaaS support triage. Built on production voice infrastructure with fallback logic.
AI-powered WhatsApp flows for sales, support, and operations. Powered by or integrated with Waaru — our own WhatsApp AI platform, so we are building on infrastructure we operate ourselves.
Document intelligence, internal knowledge bases, enterprise search, and multi-source retrieval pipelines. Proper chunking, embedding, retrieval evaluation, and cross-tenant security. We test for leakage before we ship.
n8n, Make, and custom integrations. Back-office automation, CRM enrichment, reporting pipelines, document processing. Systems that run without a human in the loop and alert when something goes wrong.
AI-powered customer support, ticket routing, knowledge base automation, and agent assist. Built by engineers who have worked inside Zendesk — we know the platform, not just the API.
Model Context Protocol integrations connecting AI agents to internal systems, databases, and third-party tools. Extend your existing LLM applications without a rebuild.
Four principles that decide what we say yes to — and what we say no to — every week.
Not a body shop. We take responsibility for what we build working in production — not just in the demo. SLA, monitoring, and handover documentation are part of every engagement.
Every AI system we ship runs through the same security checks we offer as a standalone audit. Auth, RLS, prompt injection surface, RAG leakage, agentic tool permissions. If we would find it in an audit, we do not ship it.
Waaru is our own WhatsApp AI SaaS. We have seen what breaks in production AI. We build for that, not for the pitch deck.
LangGraph for stateful multi-agent workflows. CrewAI for task-oriented agent teams. n8n for workflow automation. Not “we use the best tools.”
Two recent engagements that show the pattern — built fast, hardened properly, and still ours to look after.
AI-powered guest experience — WhatsApp concierge, booking workflows, PMS integration. Live across the property today.
WhatsApp AI for sales, support, and ops on a multi-brand D2C platform. Built on Waaru, operated by the same team that built it.
Every build ends with one of three next moves. We tell you which one fits before the engagement closes — so the next step is a decision, not a sales call.
Most teams keep us on after launch for production AI ops — quarterly red team, drift monitoring, model upgrade review, and incident support.
Already have a system and want it pressure-tested before go-live? Run the audit as a standalone engagement — same team, different lens.
DPDP exposure, model registers, and incident runbooks can be written alongside the build — not after a regulator asks for them.