AI does the work
Your team stays in control
Claude Code
Codex
OpenClaw
HermesGive any agent email, tools, memory, approvals, and monitoringit runs real business work, with every sensitive action waiting on your team's approval.
Any service through unified credits
LinkedIn
Hunter.io
Affinity CRM
Salesforce
HubSpot
Pipedrive
Gmail
Outlook
Slack
Notion
Crunchbase
Apollo
Clearbit
Specter
Google Analytics
Stripe
GitHub
Google CalendarLinkedInHunter.ioAffinity CRMSalesforceHubSpotPipedriveGmailOutlookSlackNotionCrunchbaseApolloClearbitSpecterGoogle AnalyticsStripeGitHubGoogle Calendar
Twitter/X
Medium
WordPress
Zapier
Webhooks
HTTP/REST
Google Sheets
Airtable
Microsoft Teams
Google Trends
Web Scraper
Puppeteer
Claude AI
GPT
Gemini
Mistral
DeepSeek
ComposioTwitter/XMediumWordPressZapierWebhooksHTTP/RESTGoogle SheetsAirtableMicrosoft TeamsGoogle TrendsWeb ScraperPuppeteerClaude AIGPTGeminiMistralDeepSeekComposio
Claude Code connected
Opus 4.6 Β· agentled-mcp-server
Checking workspace memory, tools, and approval rules before acting.
* agentled kg:query "fintech CTOs Europe"
-> 847 contacts Β· last enriched 3 days ago
* agentled memory:recall "outbound-eu"
-> 3 prior runs Β· best channel: LinkedIn
* agentled create "Lead prospecting for fintech CTOs"
-> 3 workflows Β· approvals enabled
43 leads scored Β· 5 high-intent Β· 38 drafts queued
Portal: agentled.app/workspace/runs
Give your agent a goal.
It handles the rest.
Not another prompt box. A supervised loop where work comes in, your agent runs it on real rails, and your team stays in control
Connect your agent.
Give it a business goal.
Connect
Install AgentLed in Claude Code, Codex, or any MCP agent.
Set the goal
Describe the outcome. AgentLed builds and runs the workflow.
Approve & improve
Review sensitive actions. Feedback becomes memory.
Your agent alone vs.
your agent + AgentLed.
Your AI agent can reason, code, and plan. AgentLed gives it the working layer: managed agents, email and team channels, any service it needs, durable memory, supervised workflows, approvals, monitoring, and ROI.
| Capability | Agent alone | Agent + AgentLed |
|---|---|---|
| Tools, channels, and credits | Your agent can suggest the workflow, but you still assemble API keys, auth, rate limits, subscriptions, and vendor bills. | Any service your agent needs through one credit pool, one workspace, and one bill. |
| Managed agents and workflows | The agent writes scripts or drafts. Agent identity, inboxes, schedules, retries, state, and handoff remain your problem. | The agent deploys managed agents and supervised workflows with cache, retries, approvals, and managed heartbeats. |
| Business memory | Context windows reset. The agent loses ICP rules, scoring rubrics, prior approvals, and outcomes. | Knowledge Graph stores entities, scores, approvals, decisions, and outcomes across every run. |
| Channels | Drafts, Slack alerts, WhatsApp follow-up, and customer threads stay scattered across tools. | Agent inbox, agent email, Slack/WhatsApp notifications, and customer-facing handoff live in the workspace. |
| Approvals | Approvals happen in chat. No durable record of who approved what or why. | Approval queues pause sensitive actions before sends, CRM updates, publishing, or customer-facing work. |
| Monitoring | Terminal logs. You become the audit trail and reconstruct failures manually. | Run history, step inputs/outputs, exceptions, credit use, and owner actions are traceable. |
| ROI portal | ROI is a spreadsheet you update later, detached from the workflow runs. | Portal shows credits, tokens, hours saved, cost avoided, pipeline influenced, and review outcomes. |
Give every agent an inbox, an email, and team channels.
Give agents managed channels for replies, alerts, and handoffs. Every email, Slack alert, and WhatsApp escalation stays attached to the workflow run that created it.
Growth Agent
growth@company.agentled.ai
agent@company.agentled.ai
3 replies need review
Slack
#sales-ops
Daily run summary posted
Agency owner alerts
Qualified reply escalated
Unified agent inbox
LiveFounder reply
Asked for revised pricing after SEO preview
Slack alert
Outbound workflow found 5 high-intent accounts
WhatsApp note
Client approved full GBP report
Approval queue
Send 12 personalized founder follow-ups
Email Β· waits for owner
Update CRM stage for 5 qualified accounts
HubSpot Β· waits for owner
Low-confidence investor fit score
Deal flow Β· waits for owner
Deployment ROI
Hours saved
84
Cost avoided
$12.4K
Pipeline influenced
$38K
Approval rate
91%
Let agents act, but keep the business in control.
Sensitive actions pause before they hit customers or systems of record. Owners approve, exceptions are tracked, and ROI stays visible from the same portal.
Teams are building managed agents with AgentLed.
Examples of managed agent workflows being built and deployed with AgentLed. The agent gets the goal; AgentLed supplies managed agents, workflow runtime, tools, memory, approvals, monitoring, and the ROI portal.
Inovexus β VC Managed Agents
inovexus.com
Client goal
βHelp our investment team source, score, and match companies with the right investors or mentors while the system remembers every decision.β
Workflow deployed
Inovexus is deploying managed AI agents with AgentLed to support startup sourcing and investor matching. Agents monitor deal channels, score companies against the investment thesis, recommend relevant investors or mentors, and generate approval-ready reports so the team keeps control while every decision is remembered.
Outcome
Pilot deployment in progress across startup sourcing, thesis-based scoring, investor recommendations, and approval-ready reports.
Agwanet β Agency SEO Workflow
agwanet.com
Client goal
βTurn our local SEO consulting offer into a repeatable Google Business Profile lead-gen workflow.β
Workflow deployed
Agwanet used the AgentLed CLI to build and run a Google Business Profile lead-gen workflow for local-business SEO leads. The agent generates a preview report, queues teaser outreach, gates the full report after payment, and creates an upsell path into the agency's SEO services. Agwanet is now connecting AgentLed into Hermes so its own agent can deploy new AI integrations, trigger SEO workflows, and monitor results.
Outcome
First workflow running in one day, with payment-gated reports and an upsell path into agency services.
These are two examples. More clients are building custom AgentLed deployments with connected tools, private data, approval gates, and integrations across their existing stack.
One API key. Any service your agent needs.
No more juggling API accounts. Every integration runs on AgentLed credits, with 300 free credits to start.
| Capability | Credits | What you'd need otherwise |
|---|---|---|
| LinkedIn company enrichment | 50 | LinkedIn API ($99/mo+) |
| Email finding (Hunter) | 5 | Hunter.io ($49/mo) |
| AI analysis (Claude/GPT) | 10β30 | OpenAI API key + billing |
| Web scraping | 3β10 |  Apify account + actors |
| Image generation | 30 | DALL-E / Midjourney sub |
| Video generation (8s) | 300 |  RunwayML ($15/mo+) |
| Knowledge Graph storage | 1β2 |  Custom database setup |
Prioritize tokens for high-ROI work.
Every run is attributed by model, app, workflow step, and agent so teams can allocate monthly-plan credits against hours saved, operating cost avoided, or revenue unlocked.
Plan credits allocated
8,420
Runs
126
Token drivers Β· Current refresh cycle Β· Jun 1-Jul 1, 2026
ROI view: 84 hours saved Β· $12.4K cost avoided Β· $38K pipeline influenced
Models
GPT-5.5
openai
2,380 cr Β· 74 runs
Claude Opus
anthropic
1,840 cr Β· 31 runs
Gemini 3 Pro
940 cr Β· 52 runs
Mistral Small 4
mistral
280 cr Β· 9 runs
Apps with attribution
Profile enrichment
1,260 cr Β· 42 runs
Firecrawl
Web extraction
890 cr Β· 36 runs
Personal follow-up
520 cr Β· 28 runs
KG Memory
Read and update
410 cr Β· 96 runs
Steps
Match ICP
Account fit
1,680 cr Β· 18 runs
Read Signals
Recent context
1,320 cr Β· 42 runs
Write Touch
Personalized
980 cr Β· 34 runs
Save Memory
Next action
620 cr Β· 32 runs
Agents
Warm ICP SEO
Finds best-fit leads
1,480 cr Β· 16 runs
Signal Scout
Reads buying triggers
1,120 cr Β· 24 runs
Content Manager
Writes 1:1 assets
760 cr Β· 18 runs
Reengagement Lead
Remembers next step
520 cr Β· 37 runs
Start with 300 free credits, then allocate credits where ROI is highest.
Agents that remember,
learn, and improve.
Your agent uses workflows behind the scenes β and persistent memory to get smarter over time. Two layers:
Not just automation β a system that gets smarter with every run.
Learn more about Knowledge GraphKnowledge Graph
847 entities Β· 2,340 relationships
Recent Activity
Compound Learning
Investor scoring accuracy improving with each execution
| n8n / Zapier | AgentLed | |
|---|---|---|
| Remembers last run | β | β |
| Cross-workflow memory | β | β |
| Compound scoring | β | β |
| Prediction vs outcome | β | β |
| Learns from results | β | β |
| One API key for any service | β | β |
Every other tool starts from zero.
n8n runs the same workflow with no memory of previous results. Custom scripts need you to build and maintain your own database.
AgentLed's Knowledge Graph stores every insight, score, and outcome automatically. Each run compounds on the last. After 12 runs, our investor scoring went from 62% to 89% accuracy β with zero manual tuning.
See how it worksStart with one managed agent.
Scale into an operating layer.
You do not need full autonomy on day one. Start with an email request, a managed agent, tools, and review. Then add memory, channels, monitoring, and ROI visibility as trust grows.
Give the agent tools
Connect the first app or data source and let the agent complete one supervised business task while you inspect every step.
One goal, one agent, one owner.
Add memory and approvals
Store the rules, examples, and outcomes in the Knowledge Graph. Pause sends, CRM updates, and customer-facing work for review.
The agent runs. Owners approve.
Run across channels
Give the agent an inbox, email address, Slack alerts, WhatsApp escalation, and monitored schedules across your client workflows.
Work reaches the right channel.
Measure ROI and expand
Use the portal to track credits, hours saved, approvals, exceptions, cost avoided, and which agent capability should be deployed next.
Each deployment compounds.
Not sure where to start? Book a strategy call β we'll map the first deployment path in 30 minutes.
Managed agents that keep working.
NEW β Agent orchestration
Define the agent, give it email and team channels, connect tools, and set the approval rules. It can run on demand or on a heartbeat, then bring customer-facing actions back to your team before anything sensitive ships.
Deal Sourcing Agent
Human-supervised Β· heartbeat: every 48h
Connected workflows
- β deal-sourcing-specter
- β deal-sourcing-linkedin
- β daily-deal-flow
Agent
Found 8 new deals this week. 2 need your review.
Get started fast
Deployment examples.
Customize as you go.
Pre-built examples for common managed-agent deployments. Pick one later, tell your agent what to change, and keep the core homepage focused on the deployment story.
Become an AI-native
organization.
Companies that build AI into their infrastructure will compound faster over the next decade. AgentLed helps you move from experiments to managed agents that operate inside your real tools, data, approval paths, and customer workflows.
Start with one custom deployment, then expand into reusable agent capabilities: integrations, Knowledge Graph memory, monitored runs, approval gates, ROI reporting, and a portal your team can supervise.
FAQ
Questions teams ask before starting
Do we need engineers to launch workflows?
For most workflows, no. AgentLed is designed for operations teams. For complex environments with custom security requirements, IT review may be needed, but the build itself does not require engineering.
How long until we see results?
Simple agent work can start in minutes once the agent and tools are connected. Serious production rollouts keep improving over days and weeks as approvals, monitoring, memory, and ROI feedback harden.
What happens if a workflow step fails mid-run?
AgentLed maintains deterministic state at every checkpoint. If step 14 of 20 fails, the system retries from step 14 with full context. No data is lost. No restart from scratch.
How is this different from n8n, Make, or Zapier?
Those tools are trigger-action chains without built-in AI reasoning, a knowledge graph, or shared business context. AgentLed orchestrates multi-step workflows where an AI agent reasons, decides, and learns β with integrated model credits, parallelization, and team collaboration.
How is this different from using ChatGPT or Claude directly?
Prompt tools have no workflow state, no system integrations, no team visibility, and no calibration. Each conversation starts from zero. AgentLed turns that one-shot interaction into a durable, improving, collaborative workflow.
Can we use AgentLed to deliver results to our own clients?
Yes. White-label portals let your clients access reports, scores, and recommendations under your brand. Your clients see your company, not AgentLed.
What models does AgentLed use?
AgentLed supports multiple models and routes to the best model for each workflow step. Document analysis, scoring, and text generation can each use different models. Model credits are included.
What happens to our data?
Your data is never used to train generalized AI models. Processing is scoped to your account. GDPR-compliant. Full audit trail. Export and data portability options are available.
What is AgentLed?
AgentLed is a supervised workspace for managed AI agents. Your agent can use email and team channels, any service it needs through unified credits, persistent memory via a Knowledge Graph, approvals, monitoring, and ROI reporting from Claude Code, Codex, Hermes, OpenClaw, or any MCP client.
How much does AgentLed cost?
Start with 300 free credits. Pro starts at β¬23.90/month for 2,000 credits. Teams starts at β¬86.90/month for 7,000 credits with unlimited members. Enterprise pricing is custom. Credits are shared across your workspace β no per-seat fees.
Is there a free trial?
Yes. Start with 300 free credits so you can connect an agent, try supervised work, and test the tools you need before upgrading.
Does AgentLed work with Claude Code, Cursor, or Codex?
Yes. AgentLed is MCP-native. Run npx -y @agentled/mcp-server to connect any MCP-compatible client β Claude Code, Codex, Cursor, or Windsurf β and create, manage, and execute agents and workflows directly from your AI coding environment.
What integrations does AgentLed support?
AgentLed connects to the services your deployment needs, including LinkedIn, HubSpot, Salesforce, Slack, Notion, Gmail, Google Calendar, Crunchbase, Hunter.io, Apify, OpenAI, Anthropic, Gemini, Mistral, web scraping, HTTP requests, and more. All accessed via a single unified credit system.
Can I import my existing n8n workflow?
Yes. AgentLed has a built-in n8n import tool. Export your workflow from n8n as JSON and import it directly β AgentLed maps the nodes to equivalent actions and shows a preview before committing.
Is AgentLed open source?
The MCP server and CLI are open source and available on GitHub at github.com/agentled/mcp-server. The core platform is proprietary. You can self-host the MCP server while using the managed platform for workflow execution and storage.
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