AI integrations

Our studio builds AI integrations that survive contact with production — not slick demos that fall over the moment a real customer messages outside business hours. Hamid leads architecture review on every brief; the senior team builds and ships. The brief is always the same: identify the workflow eating staff time, then automate it cleanly with the right model and the right people on it with the right model, the right data, and a graceful hand-off to a human when the agent is out of its depth.

Who this is for

Service businesses leaking leads after hours, ecommerce teams stuck in copy-paste hell, in-house marketers writing the same FAQ reply for the fortieth time. If you can name the workflow that shouldn’t be manual any more, an integration usually pays back its build cost within a quarter.

What gets built

Lead-capture + qualification agents

A 24/7 chat or voice intake that asks the same diagnostic questions your sales team asks, qualifies the lead, and drops it into your CRM with a structured summary. WhatsApp, web chat or phone — wherever the lead actually shows up.

Content + research pipelines

n8n-based workflows that take a topic, do the desktop research, draft to your brand voice, and post a structured draft to Notion or your CMS. Reduces a 3-hour content cycle to a 20-minute editorial review.

Customer-support copilots

Retrieval-grounded agents that answer support questions using your docs, your past tickets and your product data — not generic web content. The graceful fall-back to a human ticket is part of the build, not an afterthought.

The stack

• Models: OpenAI, Anthropic, Google Gemini, ElevenLabs — chosen per task, swappable when something better ships.
• Orchestration: n8n self-hosted or cloud, for transparent workflow logic you can audit.
• Grounding: retrieval over your own data — products, FAQs, ticket history — so the agent does not hallucinate.
• Integrations: HubSpot, Pipedrive, Klaviyo, Slack, Twilio, WhatsApp Business, Stripe — the standard pieces, wired in cleanly.

Timeline + investment

Most integrations ship in 2–6 weeks with a fixed build price from $2,500. Model-API costs are passed through transparently — typically $10–$80 per month for a small-business workload. After the discovery call you receive a written architecture and a real delivery date.

What about data privacy?

Where possible I use providers that contractually do not train on your data (OpenAI Enterprise, Anthropic, EU Gemini). Sensitive workflows can run on a self-hosted model — that architecture choice is part of the discovery, not a sales upsell.