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AI Agent SystemsBusiness AutomationRAG ChatbotsVoice + WhatsApp AgentsCustom AI WorkflowsCustom Web AppsE-Commerce PlatformsAPI + Backend BuildsDatabase ArchitecturePerformance OptimizationAI Agent SystemsBusiness AutomationRAG ChatbotsVoice + WhatsApp AgentsCustom AI WorkflowsCustom Web AppsE-Commerce PlatformsAPI + Backend BuildsDatabase ArchitecturePerformance Optimization
05c · Sub-discipline

Agent Orchestration Platform

A fleet of specialised agents, one bridge across your messaging apps.

The RedClaw / GoClaw pattern productised — a router that picks the right specialist agent, per-agent bot identities across WhatsApp, Telegram, Discord, iMessage, and a shared MCP tool gateway with audit and permissions. Buy this when you want your own multi-agent system, not just one bot.

What you get

4 pillars

Multi-agent router

One entry point classifies intent + risk and routes to the right specialist (planner, builder, reviewer, ops). Hybrid routing across providers.

Cross-channel bridge

Same agent + shared user context across WhatsApp, Telegram, Discord, Slack, iMessage. One identity, many surfaces.

Agent fleet identities

Per-agent bot identities — one Discord bot per role, separate Telegram bots, isolated tokens. Each agent has its own persona.

MCP tool gateway + audit

A shared MCP / tool registry with per-agent scoping, allowlists, audit log, and DB-backed agent registry so you add agents without code changes.

Tools we reach for

Not exhaustive
Postgres registryMCPWhatsApp CloudTelegram BotDiscord.jsClaude / GPT / Grok / Gemini

Frequently asked

4 questions

What is agent orchestration and why does it matter?

A coordination layer that decides which agent (or which model) handles a given request. With orchestration, you can route by intent, cost, latency, or capability — and fail over when one provider degrades.

Can I use multiple LLM providers — Claude, GPT, Grok, Gemini?

Yes. The platform sits behind an OpenAI-compatible gateway with provider-agnostic routing. Pick the right model per task — high-reasoning to Opus, fast classifiers to Haiku, cheap chat to GPT-4o-mini — without rewriting your app.

How is cost controlled across providers?

Per-agent budgets, per-user quotas, model fallback ladders (try cheap first, escalate on uncertainty), and per-request token caps. All requests are logged with cost attribution so you can see exactly where the bill comes from.

What happens when a provider goes down or rate-limits us?

Automatic failover to the next provider in the ladder, with no app-level changes. Health checks mark degraded models out of rotation, and the gateway retries with exponential backoff before falling back.

Sounds like the bucket you’re in?

Tell me what you’re trying to build. I’ll send a written proposal within 48 hours of our discovery call.