TheInfrastructurefor DeepAgents

While others build simple if-this-then-that automations, we built the infrastructure for deep agents - AI that can plan multi-day projects, coordinate teams of specialized agents, remember everything it learns, and improve over time. Think Claude Code, but for your entire business.

Lumnis AI Python Code Example
# Without Lumnis: 500+ lines of code, 10 different APIs, weeks of integration work
# With Lumnis: Just describe what you want in plain English
# Install: pip install lumnisai
import lumnisai
# Create client and execute complex multi-step workflow
agent = lumnisai.AsyncClient()
response = await agent.invoke(
"Pull customer tickets from Zendesk, extract product issues, " +
"query PostgreSQL for affected customers, analyze sentiment with LLM, " +
"create priority matrix in Google Sheets, generate executive report, " +
"update JIRA tickets with findings, schedule follow-up meetings in Calendar, " +
"draft personalized emails for high-priority customers, and post summary to Slack",
user_id="alice@company.com",
show_progress=True,
)
print(response.output_text)
# That's it! Lumnis handles planning, orchestration, error recovery, and coordination

Python only. Other languages coming soon.

→ View full documentation
Multi-Step Planning
Sub-Agent Coordination
Persistent Memory
1000+ Integrations
How It Works

Deep Agents vs Simple Automations

Shallow tools fail at complex tasks. Deep agents think, plan, remember, and improve - handling work that requires real intelligence.

1

Deep Agent Planning

AI that thinks before acting - creates multi-step strategies for complex tasks

Research competitors, analyze market trends, create strategic plan, monitor progress
2

Sub-Agent Coordination

Spawns specialized agents that work together with perfect coordination

Research Agent → Analysis Agent → Writing Agent → Review Agent
3

Learn & Improve

Persistent memory means agents get smarter over time

Remembers past analyses, learns patterns, improves recommendations

Deep Integration, Not Just Connections

Deep agents don't just connect - they understand and operate your tools with deep understanding. 1000+ integrations and growing.

Slack
Gmail
SQL
SharePoint
Google Drive
Salesforce
Jira
GitHub
Confluence
Notion
HubSpot
Custom APIs

The Four Pillars of Deep Agents

Planning Tool

Agents that think before acting, creating sophisticated multi-step strategies

Sub-Agent Coordination

Divide complex tasks among specialized agents working in parallel

Persistent Memory

Remember context, learn from past actions, and improve over time

1000+ Integrations

Deep access to your entire enterprise stack, not just webhooks

Self-Orchestrating

From natural language to complete execution without manual setup

Enterprise Ready

Production-grade infrastructure with security, monitoring, and scale

Why Deep Agents Beat Shallow Automations

While others offer simple if-this-then-that workflows, Lumnis AI enables deep agents - AI that plans multi-day projects, coordinates teams of specialized agents, remembers everything it learns, and improves over time. The difference between a trigger and a strategist.

User Management

Manage API users, permissions, and monitor usage in real-time.

Users

1,234

Secure

100%

Active

342

Recent Activity

alice@company.com

Created agent workflow

2 min ago

bob@company.com

Updated SQL connection

5 min ago

sarah@company.com

Deployed to production

12 min ago
Intelligent Orchestration

Watch your AI agent plan and execute multi-step workflows automatically.

Understanding
~50ms

Parse natural language intent

Planning
~100ms

Determine tools and sequence

Connecting
~200ms

Authenticate with services

Executing
~2s

Run workflow steps

Validating
~100ms

Verify results

"Analyze customer feedback and create summary report"

Real-time Analytics

Track agent performance, API usage, and business metrics in real-time.

32%
this week
14.2KAPI calls
50+ Integrations

Connect your entire stack. Just pass tool names to enable them.

OpenAI
GPT-4, embeddings, analysis
Slack
Real-time messaging & alerts
PostgreSQL
Direct SQL queries & ETL
Salesforce
Customer data & analytics
GitHub
Code review & automation
Jira
Issue tracking & workflows
Gmail
Email automation & parsing
Google Drive
Document processing & RAG
Notion
Wiki search & updates
HubSpot
Lead management & campaigns
Confluence
Documentation & knowledge base
Your API
Custom tool integration
Contextual Memory

Agents remember user preferences, past conversations, and domain knowledge automatically.

Sales Analysis Thread

2 min ago
User: Alice ChenRole: Sales Manager+1

API Development

5 min ago
Stack: Node.jsDB: PostgreSQL+1

Monthly Reports

10 min ago
Format: PDFSchedule: 1st Monday+1

Deep Agents: Built for Complex Work

Deep agents don't just react - they think, plan, and evolve. With persistent memory and sub-agent coordination, they handle complex workflows that require real intelligence, not just automation.

  • Multi-step planning and reasoning
  • Persistent memory across sessions
  • Sub-agent spawning and coordination
  • Self-improvement through learning
  • Natural language to execution
  • 1000+ deep enterprise integrations
AI Sales Intelligence

Powered by Lumnis Agents

Demo
Example: Vercel Analysis

Growth Rate

+127% YoY

Team Size

850+ employees

Market Cap

$2.25B

What Sales Intelligence Agents Do:
  • Enrich CRM data automatically
  • Track competitor movements
  • Generate personalized outreach
  • Analyze buying signals

Try it yourself:

await agent.invoke("Research Vercel and find sales opportunities")
Clear Comparison

Deep Agents vs Shallow Automations

See why deep agents are fundamentally different from traditional automation tools

Planning Capability

Shallow Tools

Linear, predetermined paths only

Deep Agents

Strategic multi-step planning that adapts

Memory & Context

Shallow Tools

Stateless - forgets after each run

Deep Agents

Persistent memory across sessions

Task Complexity

Shallow Tools

Simple if-this-then-that triggers

Deep Agents

Multi-day projects with sub-tasks

Learning Ability

Shallow Tools

Fixed logic, no improvement

Deep Agents

Learns from each execution

Error Handling

Shallow Tools

Fails on edge cases

Deep Agents

Self-healing and adaptive

Agent Coordination

Shallow Tools

Single linear flow

Deep Agents

Spawns and coordinates sub-agents

Tool Integration

Shallow Tools

Basic webhooks and APIs

Deep Agents

Deep understanding of tool capabilities

Best For

Shallow Tools

Simple, repetitive tasks

Deep Agents

Complex workflows requiring intelligence

The difference is clear: shallow tools handle triggers, deep agents handle complexity. If your workflows require planning, memory, and continuous improvement, you need deep agents.

ROI & Business Impact

What Deep Agents Deliver

Measurable business outcomes, not just technical capabilities

90%

Reduction in Integration Development Time

What took weeks now takes hours. Ship AI features faster.

10x

Complex Workflow Capability

Handle workflows impossible with simple automations.

24/7

Autonomous Operation

Deep agents work continuously, improving with each run.

75%

Fewer Failed Automations

Self-healing agents that adapt to edge cases.

Deep agents aren't just faster than manual work - they enable entirely new workflows that were previously impossible. The ROI isn't just in time saved, but in capabilities gained.

Perfect For

Who Needs Deep Agents?

Deep agents aren't for everyone. They're for teams tackling complexity that shallow automations can't handle.

AI Engineers at Non-AI Companies

Tasked with "bringing AI to production" but drowning in infrastructure work? Get deep agents without building the plumbing.

Engineering Teams with Complex Processes

Spending more time on integrations than core product? Deep agents handle the orchestration so you can focus on what matters.

Companies Beyond Simple Automation

Hit the limits of if-this-then-that tools? Deep agents handle multi-day projects, strategic planning, and continuous improvement.

VP of Engineering/Operations

Need sophisticated AI automation but can't hire an AI team? Enterprise-ready deep agents, no AI expertise required.

You Need Deep Agents If...

Your automations keep breaking on edge cases
You have processes too complex for flowcharts
You need AI that improves without retraining
Your team is building the same integrations repeatedly
Simple triggers can't handle your use cases
You need multi-day planning and execution
Core Capabilities

The Five Pillars of Deep Agents

Built with planning, memory, coordination, integrations, and MCP-powered reasoning - these five pillars enable deep agents to handle complex tasks that simple automations can't even attempt.

Planning Tool - Agents That Think

Deep agents plan before acting, creating sophisticated multi-step strategies

Multi-Day Project Planning
Unlike simple triggers, deep agents can plan and execute projects spanning days or weeks, adapting strategies as they progress.
Strategic Reasoning
Breaks down complex goals into executable steps, considers multiple approaches, and selects optimal paths based on context.
Dynamic Adaptation
Plans evolve based on results. When one approach fails, agents replan and try alternative strategies automatically.
Natural Language Understanding
Describe complex objectives in plain English. Deep agents understand intent and create comprehensive execution plans.

Sub-Agent Coordination - Teams of Experts

Divide and conquer complex tasks with specialized agents working together

Automatic Agent Spawning
Deep agents spawn specialized sub-agents for specific tasks - research agents, analysis agents, writing agents - all coordinating seamlessly.
Parallel Task Execution
Multiple agents work simultaneously on different aspects of a problem, dramatically reducing time to completion.
Expert Agent Library
Pre-built specialized agents for common tasks: data analysis, report generation, code review, market research, and more.
Intelligent Handoffs
Agents pass context and results between each other intelligently, ensuring seamless collaboration and efficiency.

Persistent Memory - Agents That Learn

Remember, learn, and improve over time through continuous experience

Cross-Session Memory
Unlike stateless automations, deep agents remember past interactions, building knowledge that compounds over time.
Pattern Recognition
Agents identify patterns in data, user preferences, and successful strategies, becoming more effective with each task.
Contextual Learning
Learn from failures and successes. Agents adapt their approach based on what worked before in similar situations.
Knowledge Synthesis
Combine learnings from multiple tasks and sessions to develop deep domain expertise unique to your business.

1000+ Integrations - Deep, Not Just Connected

True integration means understanding and operating tools like an expert user

Beyond Simple APIs
Deep agents don't just connect - they understand tool capabilities, best practices, and can navigate complex workflows within each system.
Enterprise Tool Mastery
From Salesforce to Slack, SharePoint to ServiceNow - agents master every feature and capability of your tools.
Custom Integration Framework
Easily add your proprietary tools and systems. Deep agents learn to use them as effectively as pre-built integrations.
Unified Data Access
Agents seamlessly work across all your tools, synthesizing information from multiple sources to complete complex tasks.

Bring Your Own MCP - Multi-Step Reasoning

Leverage Model Context Protocol servers for advanced multi-step problem solving

MCP Server Integration
Seamlessly integrate your own Model Context Protocol servers to extend agent capabilities with domain-specific expertise and tools.
Multi-Step Reasoning Engine
Break down complex problems into logical steps, with agents reasoning through each phase using MCP-powered context and capabilities.
Custom Tool Development
Build and deploy your own MCP tools and servers, giving agents specialized abilities tailored to your unique business needs.
Context-Aware Problem Solving
MCP servers provide rich context that enables agents to understand nuanced requirements and deliver sophisticated solutions.

Ready for Deep Agents?

Stop building AI infrastructure. Start shipping deep agents that plan, remember, and improve. See the difference in minutes.

Deep Agent Infrastructure

Enterprise-Grade Deep Agents

The only infrastructure built specifically for deep agents - with planning, memory, coordination, and scale that shallow automations can't match.

Performance Metrics

Planning Depth

Multi-day strategies

100+ steps

Sub-Agent Spawning

Parallel execution

Unlimited

Memory Persistence

Cross-session learning

Infinite

Integration Depth

Enterprise tools

1000+

Concurrent Agents

Per organization

10,000+

Learning Cycles

Self-improvement

Continuous
Security
Enterprise-grade security
End-to-end encryption
Encryption at rest
SSO support
Role-based access control
Audit logs & controls
Private deployment options
API Capabilities
Natural Language Instructions
Deep Agent Orchestration
Multi-Agent Coordination
Persistent Memory Management
Real-time Progress Streaming
Planning & Strategy Visibility
Learning Pattern Tracking
Sub-Agent Communication
Deep Agent Use Cases

Complex Work That Shallow Tools Can't Handle

Deep agents handle multi-day projects, strategic planning, and continuous learning - work that would fail with simple if-this-then-that automations

Frequently Asked Questions

Ready for Deep Agents?