Your AI Agents,
Your Rules.

Build customer-facing and internal AI agents in minutes, with governed deployment when your team is ready.

& any industry...
Preview an agent blueprint before signup · No account required
Governed tools
Actions stay within scope

Connect knowledge and tools with clear owner review before the agent performs sensitive work.

Deployment controls
Launch when the team is ready

Move from preview to widget, API, or managed deployment with visible state and rollback expectations.

Evaluation evidence
Readable confidence signals

Use scenario checks, docs, and research notes to understand what the agent is ready to handle.

Agent workflows

Launch useful agents without starting from a blank prompt

AgentNexus helps SaaS teams preview, ground, test, and launch agents for customer support, onboarding, operations, and knowledge workflows.

Research Assistant

Turn market, product, or support questions into concise briefs your team can review.

Starting point

Market brief, competitor set, technical question, or decision context.

Agent outcome

Research brief with assumptions, risks, and next actions.

Blueprint Builder

Turn a URL, product idea, or business process into an agent blueprint and implementation path.

Starting point

Website URL, product thesis, target user, or workflow description.

Agent outcome

Agent blueprint with audience, knowledge needs, guardrails, and launch path.

Internal Operations

Give teammates an agent that can follow approved process, collect context, and prepare next actions.

Starting point

Internal workflow, support process, account question, or QA concern.

Agent outcome

Structured answer, owner handoff, and review path.

Knowledge Agent

Load repositories, specifications, skills, and runbooks as operating context instead of starting each session cold.

Starting point

Repo docs, local skills, SOPs, support knowledge, and project constraints.

Agent outcome

Grounded responses that stay aligned with approved team material.

Workflow Agent

Coordinate tools, scripts, APIs, and multi-step agent procedures through inspectable execution paths.

Starting point

Repeatable process requiring tool use, handoffs, or production verification.

Agent outcome

Inspectable workflow with checkpoints, owner boundaries, and outcomes.

Evaluation Agent

Check agent behavior against scenarios, safety expectations, and launch-readiness criteria.

Starting point

Scenarios, expected behavior, scoring rubrics, and safety requirements.

Agent outcome

Comparable evaluation results with pass/fail evidence.

Why AgentNexus

AI Agents That Actually Work

Most AI tools give you a chatbox. AgentNexus gives you a complete agent platform — with knowledge management, conversation memory, deployment tools, and a CLI for automation.

Whether you're a solo founder automating customer support, or an enterprise deploying 50 specialized agents — AgentNexus scales with you. Powered by the best LLMs, managed by your rules.

"Build once. Deploy everywhere. Let your agents do the work."
AgentNexus Dashboard — AI Agent Management Platform

Launch workflow

From blueprint to governed launch

Start with an agent blueprint, review the knowledge and boundaries, test the experience, and launch only when the owner and workflow are clear.

Initialize/Branch/Checkpoint/Promote
01

Initialize Context

Collect user intent, repository state, skills, documentation, environment details, and constraints before the agent takes action.

02

Create a Task Branch

Convert the request into a bounded execution branch with scope, assumptions, risk checkpoints, and verification criteria.

03

Execute with Tools

Use shell, APIs, browser automation, eval harnesses, codebase edits, and deployment workflows within the declared branch.

04

Checkpoint Evidence

Capture tests, build output, browser smoke, health checks, eval scores, and production observations as branch evidence.

05

Promote or Iterate

Promote the work when gates pass, or keep iterating with the evidence preserved in docs, runbooks, and append-only audit trails.

Platform controls

Controls buyers and builders can both understand

AgentNexus keeps the public story simple while giving technical reviewers a path into docs, research, and deployment controls.

Repository Context

Control

Agents inspect architecture, file ownership, tests, conventions, and dependency boundaries before modifying a project.

Operational effect

Changes fit the existing system instead of behaving like isolated generated code.

Skill Policies

Control

Local skills encode operating procedures, QA gates, deployment rules, and domain-specific constraints.

Operational effect

Agent behavior becomes repeatable, governed, and aligned with how the team actually works.

Tool Orchestration

Control

Agents coordinate approved knowledge, workflows, integrations, and team review steps.

Operational effect

Plans become executable workflows with observable intermediate states.

Verification Hooks

Control

Meaningful work can be checked through tests, builds, browser events, production checks, and scored evals.

Operational effect

Teams can inspect proof instead of accepting model confidence as the final answer.

Operational Memory

Control

Runbooks, skills, docs, and result logs preserve project knowledge outside transient chat context.

Operational effect

Every production lesson can make the next agent run safer and faster.

Approval Boundaries

Control

Routine work can proceed quickly while destructive, security-sensitive, or ambiguous changes require alignment.

Operational effect

Automation stays accountable without slowing every low-risk task.

Evaluation gates

Evaluation evidence for agent reliability

AgentNexus treats agent output as product behavior. Critical workflows should be checked against scenarios, boundaries, and review paths before they are trusted.

Gate dimensions

  • Scenario coverage and task completion
  • Blueprint validity and output relevance
  • Tool, prompt, and safety boundaries
  • Browser and runtime failure signals
  • Production readiness and rollback confidence
GateSignalArtifact
Scenario Eval
Scored behavior
Production evals record pass rates, failure detail, and append-only audit rows.
Browser Smoke
Hidden-failure detection
Smoke captures console errors, page errors, failed requests, and 400+ responses.
Build Gate
Release readiness
Automated checks and launch review keep product changes from relying on guesswork.
Audit Trail
History preserved
Eval TSVs, runbooks, and deployment notes preserve decisions instead of hiding mistakes.

Fleet operations

Operations for teams running more than one agent

AgentNexus is built for teams operating customer-facing and internal agents across real workflows rather than one-off chat sessions.

Deploy Workloads

Operate included AgentC Runtime and Hermes cloud agents with visible lifecycle state, health checks, rollback controls, Tool Gateway evidence, and browser QA evidence.

  • AgentC Runtime/Hermes managed deployment with production pilot evidence
  • NanoBot and OpenFang shown as WIP roadmap runtimes
  • Lifecycle timeline, diagnostics, and cleanup controls

Operate Agent Fleets

Keep multiple agents and workflows observable after launch through logs, eval history, and runbook discipline.

  • Skill and runbook enforcement
  • Regression-aware eval history
  • Dedicated tracks for warning and performance debt

Govern Risk

Separate routine execution, security-sensitive changes, dependency risk, and human authorization boundaries.

  • Approval gates for high-risk actions
  • Auditable production change records
  • Separate dependency and security remediation workflows

Production control surface

Security, reliability, and cost of change are managed through operating controls, not vague promises.

  • Authenticated execution paths
  • Least-privilege access boundaries
  • Auditable decisions and eval records
  • Human authorization for high-risk actions

Harness the Power of Industry-Leading Cloud SaaS

CloudflareCloudflare
SupabaseSupabase
StripeStripe
AnthropicAnthropic
OpenRouterOpenRouter
GitHubGitHub
VercelVercel
Google CloudGoogle Cloud
DockerDocker
RailwayRailway
DiscordDiscord
PostgreSQLPostgreSQL
CloudflareCloudflare
SupabaseSupabase
StripeStripe
AnthropicAnthropic
OpenRouterOpenRouter
GitHubGitHub
VercelVercel
Google CloudGoogle Cloud
DockerDocker
RailwayRailway
DiscordDiscord
PostgreSQLPostgreSQL

Operational Cost

Hosted Cloud Agents, Not Just Chat Credits

Advanced is the primary production plan. Starter is a light production entry point; every plan is built around hosted AgentC Runtime/Hermes agents, Tool Gateway reads, deploy lifecycle, command/workspace operations, and explicit credit packs.

MonthlyAnnual

Starter

$29.90/mo
7-day free trial included
  • Light production entry for one agent
  • 1 included AgentC Runtime/Hermes deploy slot
  • Cited web search and Public GitHub repo import
  • Google Workspace OAuth read actions
  • 2,000 credits/mo with 3-cycle rollover
  • No raw shell/browser by default

Advanced

$299/mo
7-day free trial included
  • Primary production plan for teams
  • 10 included AgentC Runtime/Hermes deploy slots
  • 20,000 credits/mo with 3-cycle rollover
  • Per-agent cost, uptime, and slot dashboard
  • Beta ephemeral cloud sandbox for repo demos
  • Calendar, Sheets, and Drive writes with approval
  • Developer Mode request path

Enterprise

Custom
  • Managed Browser approval-gated pilot with domain allowlists
  • Gmail send approval and sensitive-action audit
  • Session screenshots and audit logs
  • Developer Mode diagnostic access with review and kill switch
  • SSO, custom security, and support review
  • White-label and dedicated cluster options

Credit packs: buy 1,000-100,000 extra credits at $0.01/credit through Stripe Checkout. Stripe-hosted stablecoin checkout is available for credit packs where approved. Rollover: unused included credits carry forward for 3 completed billing cycles.

Join the Beta Network

Access the next generation of autonomous operations. Currently by invitation only.

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