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agent-orchestrator — session

$ orchestrate --deploy --agents=all

Your workflows, orchestrated by agents

We build multi-agent LLM systems that automate your most complex processes. From intake to output, end-to-end.

12 agents deployed
4.2M tasks processed
99.9% uptime

Four panes. One orchestration layer.

[orchestrator]
services logs config
14:32
~/services/architecture $
Agent architecture
Process mapping, agent selection, and pipeline design. We build the blueprint before writing code.
timeline1–2 weeks
outputArchitecture doc
stackClaude, GPT-4o, LangGraph
~/services/integration $
Build + integrate
Full development with deep connections to your CRM, ERP, databases, and APIs.
timeline2–4 weeks
outputRunning system
stackREST, webhooks, connectors
~/services/monitoring $
Monitor + optimize
Performance dashboards, error handling, cost management, and model upgrades.
timelineOngoing
outputSLA-backed ops
stackLangfuse, dashboards, alerts
~/services/handoff $
Training + handoff
Documentation, training sessions, and structured transfer for your team to own it.
timeline1 week
outputDocs + training
stackNotion, Loom, live sessions
"orchestrator" 4 panes (2x2) all services operational

Deployment reports from the field

Real feedback from teams running agent systems in production.

Client report 2025-01-15 09:42 UTC

"They mapped our entire support workflow in a week and had agents handling 80% of tickets within a month. Our team now focuses on complex cases instead of repetitive triage."

Client report 2025-02-03 14:18 UTC

"We went from 6 people triaging support emails to 1 person reviewing agent decisions. The accuracy is higher than what we had before."

Client report 2025-03-12 11:05 UTC

"Invoice processing went from 3 days to 4 hours. Zero manual input. The ROI was obvious within the first week."