AI agents and multi-agent systems that automate complete business processes
An AI 'boss' coordinates multiple agents to execute an end-to-end process without micromanagement.
LangGraph orchestration with orchestrator agent, sub-agents with MCP tools, shared memory/state, queues, and end-to-end observability.
Reads PDFs, extracts data, and generates orders/invoices connected to your inventory.
Structured extraction + validations; MCP connectors to ERP/Inventory; traceability and policy checks.
Automated flows with clear routes; AI classifies, summarizes, and reports.
n8n/Genkit for flow core; specific AI nodes; webhooks/DB; versioning and auditing.
Finds prospects and sends emails that sound human and relevant.
Enrichment (external APIs), templates with guardrails, LLM with brand profile, limits and warm-up; CRM synchronization.
A chat that understands context, asks questions, qualifies, and schedules.
Agent with memory, MCP tools (calendar, CRM); rules/guardrails and human handoff.
Combines signals from support, product, and sales to tell you which accounts are doing well or poorly.
Lightweight feature store; configurable scoring; multi-source ingestion; executive dashboards.
AI answers with your documents and data as a base, doesn't make things up.
ETL pipelines, vectors + re-ranking, LightRAG-style retrieval, quality evaluations, and privacy per space.
Prioritizes leads by real probability of closing.
Propensity models + hybrid rules; lightweight MLOps; drift monitoring.
Social listening to see what people think about your brand and competitors.
Capture via APIs/scraping; sentiment/topic analysis with LLM; reports and alerts.