Agent Teams

Agent Architecture for
the Next Era of Business

The infrastructure layer that lets any company — startup or enterprise — build, deploy, and operate autonomous AI workforces.

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The Problem

Every Company Needs AI Agents.
Nobody Has the Infrastructure.

Agents will make decisions, execute tasks, and operate 24/7 across every business function. But today, there's no platform to make it easy.

For Startups

Need 10+ roles to operate: eng, QA, finance, legal, sales, support

Spend $15K–50K/month on headcount before reaching product-market fit

Founders become the bottleneck — can't scale without hiring

For Enterprises

Thousands of repetitive processes across departments ripe for automation

AI adoption is fragmented — ChatGPT here, Copilot there, no architecture

No platform to orchestrate agents at scale with memory, trust, and governance

The Solution

Makana: Agent Architecture
as Infrastructure

The future of business is not humans using AI tools. It's agent organizations that think, decide, and operate — with humans steering strategy.

⚙

Deploy Agents

Provision persistent AI workers to cloud infrastructure. Each agent has identity, workspace, memory, and tools.

➜

Orchestrate Work

Agents communicate via message queues. An orchestrator assigns tasks, evaluates results, and adapts strategy.

⚡

Scale Autonomy

Progressive trust model: agents earn independence through results. From supervised to fully autonomous, with governance at every level.

Architecture

How It Works

A structured hierarchy with clear responsibilities. Humans set strategy, agents execute.

HUMAN (Strategy) | |-- Mission Control -- dashboard + management |-- Messaging -- Telegram, Slack, API ORCHESTRATOR (CEO Agent) | Reads context -> Assigns tasks -> Evaluates | |-- ENGINEERING — Dev + QA + DevOps |-- RESEARCH — Market + email intel |-- FINANCE — Bank API + categorize |-- SALES — Pipeline + proposals |-- SUPPORT — Tickets + onboarding HEALTH MONITOR (Daemon) Auto-heal -> Alert -> Report

The Agent Stack

LLM Layer — Claude, GPT, Gemini (swappable per role)
Memory Layer — Retain / Recall / Reflect (persistent)
Messaging Layer — Cloud Tasks + Pub/Sub
Provisioning — One-click deploy to any cloud
Governance — Progressive trust + audit trails
Dashboard — Mission Control (real-time)

Key Principles

Multi-LLM — best model per role, no vendor lock-in
Scripts first — deterministic where possible
Scale to zero — agents activate on-demand
Flat until bottleneck — no unnecessary hierarchy

Templates

Pre-Built Agent Teams

Deploy a fully functional agent department in minutes. No code required.

Engineering

Dev workers + QA testers + DevOps. CI/CD integration, code review, automated testing loop.

Finance

Bank API connectors + invoice processing + expense categorization + monthly reporting.

Sales

CRM sync + lead tracking + follow-up drafts + proposal writing. Pipeline on autopilot.

Legal

Contract review + compliance monitoring + regulatory change detection. On-demand, $0 when idle.

Research

Market intel + email monitoring + meeting summaries + competitive analysis. Daily briefings.

Custom

Build your own agent with any LLM, any tools, any workflow. Full SDK + MCP integration.

Economics

The Math Speaks for Itself

25x+ cost reduction — and the gap widens as models get cheaper every quarter.

Traditional Team

$25K+

Per month for a small team
Works 8h/day, 5 days/week
6 months to hire + onboard
Training, turnover, management
Scales linearly with headcount

Agent Workforce

<$1K

Per month for equivalent coverage
Works 24/7, 365 days/year
Deploy in minutes, not months
No turnover, no management
Scales by adding agents on-demand

Status

What's Built Today

Not a prototype. Operational infrastructure running in production.

Mission Control

Full dashboard: agent grid, topology view, live activity feed, terminal access, cost tracking.

Provisioning Engine

One-click deploy: create VM, install runtime, workspace + memory, systemd service, bridge deploy.

Memory System

Retain / Recall / Reflect: daily logs, entity knowledge banks, periodic consolidation across sessions.

Inter-Agent Messaging

Cloud Tasks for dispatch, Pub/Sub for reports. Agents communicate without sharing context windows.

Integration Layer

OAuth: Google, GitHub, Notion. GCP Secret Manager. MCP server config per agent. Any service.

Production Workers

Multiple agents running 24/7 on GCP: dev, ops, research. Dog-fooding the platform daily.

Built in 4 weeks. Running in production. This is not a prototype — it's operational infrastructure.

Agent Architecture forthe Next Era of Business

Every Company Needs AI Agents.Nobody Has the Infrastructure.