AI Infrastructure Built Without Compromise

An automated hiring pipeline that ingests resumes from three separate intake channels, runs them through a summarization and skills-extraction layer, scores each candidate against the open job description, and pushes matched profiles straight to the recruiter's portal. The scoring model weighs relevancy, extracted skills, and role fit before a final match pass filters out noise, so recruiters only see candidates worth a look. Built to run three parallel intake pipelines simultaneously without cross-contaminating candidate data.

A centralized routing system for a multi-brand retail group, built to take incoming customer reviews and complaints across six separate storefronts and automatically classify, route, and log each one to the correct brand's operational sheet. Conditional branching separates flagged issues from routine feedback before either path updates the right internal record, so store managers get what needs action without digging through what doesn't.

An order fulfillment backbone that geocodes every incoming delivery address on a schedule, writes confirmed order state across three separate internal portals via direct SQL execution, and fires a WhatsApp confirmation to the customer the moment the order is locked in. Paired with a Chatwoot-integrated account creation and order confirmation flow that checks for an existing customer record before deciding whether to create a new account or route to an existing one, then syncs the confirmed order to the delivery API.

A chat-based sales assistant that classifies every inbound message into one of four intent branches before deciding how to respond. Sales and prediction queries execute live SQL Server queries to pull real account or forecast data into the response, general queries route through a lighter conversational model, and anything the classifier can't confidently place gets flagged for human review instead of guessing. Each branch keeps its own memory context, so the conversation doesn't lose thread across turns.

A sourcing pipeline that pulls candidate data directly from Apollo's API on trigger, splits and processes the results, and pushes qualified leads straight into the agency's internal recruiting portal, no manual export, no CSV handoff. Built with dual trigger paths so the same pipeline handles both scheduled headhunting runs and ad hoc phone-based lookups.

A WhatsApp-native ordering assistant that accepts both text and voice messages, transcribes incoming audio, runs the order through a conversational agent backed by Groq for fast response times, and writes the order to a live sheet as the conversation happens. Voice replies are generated and sent back through the same thread, so the entire ordering experience, from 'what's on the menu' to a confirmed order, happens without the customer leaving WhatsApp.

A two-part system that separates content generation from scheduling logistics. On one trigger, it drafts and publishes job posting content automatically. On a second, independent trigger, it pulls available interview slots directly from Cal.com's API and books the interview without a recruiter touching a calendar. Keeping the two flows decoupled means a scheduling hiccup never blocks a job post from going out, and vice versa.

A lead generation system built around three separate nurture sequences, initial contact, active conversation handling, and a dedicated follow-up track, so a lead that goes quiet doesn't just fall out of the pipeline. Incoming messages are analyzed and routed through a switch layer that decides whether the next step is a booked appointment, a follow-up email, or a status update, with timezone resolution built in so booking times are correct regardless of where the lead is. Every branch updates the source sheet, so the sales team always has an accurate live view of pipeline state.