// SVC_NODE: 01
STATUS: AGENTS

AI agents that
do real work.

We build AI systems for startups that need to move faster without adding headcount. Agents, pipelines, automations — wired into your actual workflow, not bolted on top of it.

[SYSTEM_CAPABILITIES]
  • 01.AI agents with memory, tools, and decision logic
  • 02.n8n and custom automation pipelines
  • 03.LLM-powered internal workflows (document processing, lead research, data extraction)
  • 04.Multi-step agentic systems with human-in-the-loop checkpoints
  • 05.AI integrations into existing products and codebases
[SYSTEM_FLAGS]
--memory--tools--human-in-loop--multi-step--webhook-ready
[CASE_STUDY]

"Our internal AI chief-of-staff, Gus, runs on a multi-service architecture with LiteLLM routing and persistent memory. Gus handles lead screening, document processing, and pipeline staging without human intervention."

[DIAGRAM: SYSTEM_LOGIC_PIPELINE]
INPUTAGENT// DECISION_LOGICTOOLS (n8n/APIs)VECTOR_MEMORYOUTPUT
AGENT_SYS_SIMULATOR // ONLINE

What we keep seeing

01 // BRITTLE STACKS

Founders duct-taping Zapier and ChatGPT together and calling it an AI strategy.

02 // WASTED LABOUR

Hours lost to repetitive operational tasks a well-built agent would handle in seconds.

03 // MISFIT TOOLING

Off-the-shelf AI tools that almost fit — but require a workaround for every edge case.

Execution Blueprint

We do not guess. Every engagement follows a deterministic pipeline to ensure structural integrity and zero scope creep.

Phase 01 — Map

We understand what you're doing manually and what it would take to automate it properly.

Phase 02 — Scope

We define exactly what gets built, what it connects to, and what done looks like.

Phase 03 — Build

We build the system, test it against real data, and wire it into your stack.

Phase 04 — Hand off

You get the system, the docs, and the ability to run it without us.

// TERMINAL_READY

Tell us what you want to automate

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