AI infrastructure that operates.

A salon in Hoboken was answering after hours with generic 'we'll contact you tomorrow' messages. We replaced that autoresponder with an agent that understands the requested service, checks real availability and proposes 2 alternative times in <30 seconds. Result: 51% more bookings in the quarter, without adding staff.

“An AI won't sound like my brand.” The agents we build are trained on your real conversations (WhatsApp and Instagram exports), your tone guidelines and your favorite examples. Before go-live we run a review phase where you validate every response archetype. The agent isn't a generic bot: it's a junior operator trained in your voice.

Meta Cloud API (WhatsApp), Instagram Graph API, Claude 4/GPT-4 as the main LLM, tool use for calendars and CRM, Supabase for conversation history, dashboards on Vercel with near-real-time updates.

An aesthetic clinic in Union City had a receptionist dedicated to booking consultations, confirming and rescheduling. After implementing automatic scheduling with WhatsApp confirmation + 24h and 2h reminders, front-desk calls dropped 63% and no-shows fell 18 percentage points. The receptionist went from firefighting to managing what truly matters.

“My calendar is a mess, nothing can be automated.” In the first week we run a discovery that organizes your service taxonomy, real durations, buffers and priority rules. We don't automate chaos; we organize it first. If the calendar isn't ready, we tell you before quoting.

Google Calendar / Outlook / Calendly API, two-way sync with timezone handling, configurable buffer pools, rescheduling logic that respects the cancellation policy, Twilio or WhatsApp for reminders.

A real estate team in Manhattan received 300 leads a month and 75% went cold because they only reached out once. We designed a 7-touch multi-channel sequence (WhatsApp → email → SMS → retargeting → break-up) with AI that personalizes tone and timing by industry and behavior. In 4 months: 3.2× active leads in the pipeline and $1.8M of pipeline attributed directly to the sequence.

“If I send 7 messages, I'll look like spam.” Each touch adds different value: a relevant case, a calculator, a testimonial, an open question, a binary proposal. The AI decides when NOT to send if the lead shows friction. If a touch doesn't add value, it isn't sent — the rule is value, not frequency.

HubSpot / Pipedrive / custom CRM, Segment for event tracking, dynamic branching by signals, A/B testing of subject and CTA, Meta Conversions API for retargeting, multi-touch attribution in the dashboard.

A residential cleaning company migrated from a Google Sheet to HubSpot enriched with AI: every lead enters with source, industry and estimated budget inferred by an LLM from the conversation. Automated lead scoring prioritized those most likely to close and the sales team doubled monthly quotes without hiring anyone.

“I already have a CRM nobody uses. Why change?” We don't replace the CRM; we make it usable. We automate capture and enrichment so salespeople only see qualified leads with context. The friction that makes nobody use your CRM is removed: the CRM stops being a form and becomes a prioritized inbox.

HubSpot / Pipedrive / Salesforce APIs, enrichment with Clearbit/Apollo, LLM scoring over the original conversation, two-way sync with the multichannel inbox, executive dashboards.

A restaurant managed reservations over WhatsApp, Instagram DM and Messenger on 3 different phones. Staff lost conversations, duplicated replies and answered late. We consolidated the 3 channels into one inbox with an AI agent and human handoff: 4 hours a day freed for staff, zero lost messages and a 27% drop in no-shows with automatic reminders.

“I don't want my team to switch tools again.” The inbox integrates into the flow they already use; the interface can be the dashboard we build or an existing app like Kustomer or Front. What matters isn't which UI they look at, but that the 5 sources arrive in one place with full context.

WhatsApp Business API, Instagram Graph API, Facebook Messenger, SMS (Twilio / 360dialog), email over IMAP, persistence of conversation threads cross-linked by customer identity.

A clinic didn't know how many of its appointments came from Instagram vs Google vs word of mouth. We set up multi-touch attribution from first contact to closed appointment, with an executive dashboard the owner reviews for 10 minutes on Mondays. Those decisions redirected $12k monthly of ad budget toward the channels that actually converted.

“I already have Google Analytics, why more?” GA tells you how many users visited your site. Our dashboards tell you how many appointments each channel closed, how long the AI agent took in each conversation, where the funnel drops and which messages convert. It's the business layer on top of the traffic layer.

Recharts / Tremor for visualization, Supabase or Postgres as the source of truth, Segment / PostHog for events, Meta Conversions API + Google Ads API to close the attribution loop.

An insurance agency with 20 years and 40 employees wanted to 'add AI' but didn't know where. In 3 sessions we mapped 14 processes, prioritized the 3 with the highest ROI and built a 12-month roadmap with measurable gates. They avoided investing $80k in irrelevant tools and started with the quick win that paid for the rest of the plan.

“I don't need consulting, I need execution.” On projects without prior diagnosis we lose 2–3 weeks discovering real problems. Consulting is cheap compared to building something nobody uses afterward. In Retainer and Partnership it's included; in Sprint it's optional but strongly recommended.

Workshops with stakeholders, process mapping with Miro/Notion, a use-case canvas, financial ROI projection, prioritization with an impact-effort matrix and a detailed roadmap in Linear/Asana.