Multi-agent systems that reason, plan, and act to automate complete 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.
Outreach agent → more responses and meetings.
Agentic chatbot → better qualified leads.
Internal RAG → reliable and auditable answers.
Depends on the case. Can be self-hosted (on-prem) with open-source LLMs (allows fine-tuning and is more cost-effective long-term, requires investment/hardware) or cloud (AWS, Azure, GCP, Runpod) to go faster without managing infrastructure.
Yes: CRM, ERP, calendars, email, databases, and your own APIs.
SSO/OIDC, encryption, access control, auditing, secrets, and policies per environment.
We use what fits best: if you already have servers or want to reduce long-term costs, we set up AI on your own infrastructure; if you prefer speed, we go cloud.
Base stack: React, Angular, Genkit, OpenAI, DeepSeek, AWS, GCP, Azure, LangGraph, MCP, RAG. Self-hosted deployment (GPU on-prem/colocation) or cloud (AWS/GCP/Azure/Runpod). Observability, tracing, and evaluations; policy/guardrails; privacy per space/domain.