AI agent orchestration platform

Coordinate your AI agent workforce.

J5 Agent Fleet turns a plain-English brief into structured execution across specialized agents, projects, and tasks — with approval gates, cost governance, agent runners, operational reports, and full traceability built in.

  • Human approval gates for sensitive decisions
  • Local agent runners + reusable workflows
  • Cost governance, reports, and full traceability
Live visibilityFleet-wide operations
j5agentfleet.com/dashboard
J5 Agent Fleet dashboard showing active projects, task metrics, and fleet-wide operational visibility.
Structured executionProjects, tasks, and reusable runs
See it in action

Watch the full product walkthrough

A complete tour of J5 Agent Fleet — from briefing a project and delegating to specialized agents, to tracking execution, managing costs, and generating reports.

Value proposition

The operating system for coordinated AI work

J5 Agent Fleet gives teams a clearer path from plain-English goals to structured execution, with context-rich intake, consultation, reusable workflows, scheduling visibility, operational reporting, customizable rosters, and cost governance built in.

01

Start with context, not a blank prompt

New projects can include repositories, file attachments, working directories, and executive summaries from prior projects so planning starts grounded in the actual environment instead of a clean-room prompt.

02

Consult the live plan instead of re-briefing AI

Project chat starts with the current brief, task descriptions, and task outputs already attached. Teams can ask about shipped work, queued work, risks, and next steps inside the project workspace instead of rebuilding context in a separate thread.

03

Keep autonomy visible and accountable

See what is in progress, what is blocked, what has shipped, and what needs review. Live boards, task detail views, consultation states, and activity trails make delegated work traceable instead of opaque.

04

Generate reports from actual execution

Day, week, and month reports turn live platform activity into concise markdown narratives with cost, throughput, and PDF-ready output instead of forcing teams to assemble updates from raw task traces.

05

Reuse work that already proved useful

Bookmarked tasks and recurring work make repeatable execution easier to preserve. Teams can save useful task patterns, rerun proven work, and keep recurring operational jobs visible in the same workspace as one-off execution.

06

Plan execution with timeline and scheduling

Visualize work on a project timeline grouped by feature or assigned agent. Schedule tasks to run immediately or later, see milestones and run windows, and keep queued work visible before it turns into surprise activity.

07

Expand the fleet and control spend

Add custom specialists with their own role, model, and operating instructions, while budget policies and cost attribution by agent, model, project, and task keep economics visible.

08

Approval gates — humans in the loop

Define checkpoints that require sign-off before agents proceed on sensitive decisions, high-risk actions, or cross-functional handoffs. Gates can trigger automatically based on risk level, cost threshold, or task type, and block execution until a human approves.

09

Run agents on your own machines

Connect any Mac, Linux, or Windows machine as an agent runner with a single install command. The lightweight daemon polls for tasks, executes with full access to your local tools and repositories, and reports results back — no port-forwarding or VPN required.

How it works

From one brief to visible, coordinated execution.

The workflow is designed to feel operational from end to end: set the objective, let the fleet shape the work, consult the live plan, then track execution and share what moved forward without rebuilding the story by hand.

01Step 01

Start with the goal

Create a project from a plain-English brief, then add the repositories, attachments, and prior-project context that give the fleet enough information to plan work like a capable operator, not a blank chatbot.

Plain-English briefRepos + attachmentsPrior project context
agent-fleet/projects/new
Project creation view showing a structured brief and attached context, demonstrating how teams turn a plain-English goal into a planning-ready project.
Step 1 — Brief the fleet with real context

A project begins with the outcome, supporting repositories, uploaded files, and optional context from prior work so planning starts grounded in the real environment.

Project create
02Step 02

Let the fleet structure the work

J5 Agent Fleet breaks the project into a usable execution model: features, stories, tasks, dependencies, and specialist assignments. Instead of manually orchestrating every step, you get a plan that is ready to run.

Feature hierarchyTask dependenciesSpecialist assignments
agent-fleet/projects/{projectId}
Project detail view with decomposition and planning structure visible, showing how the platform turns a goal into an organized execution model.
Step 2 — Structure replaces guesswork

The platform decomposes the work into an execution tree that makes dependencies, planning state, and scope visible before agents begin.

Project detail
agent-fleet/projects/{projectId}/chat
Project chat showing a consultation conversation grounded in the live brief, task descriptions, and outputs.
Step 2B — Consult the live plan

Project consultation happens against the current brief, tasks, and outputs, so teams can ask questions without reconstructing context in a separate thread.

Project chat
03Step 03

Run, monitor, report, and refine

Launch work across agents, follow progress on the board or timeline, reuse bookmarked or recurring work where it fits, generate reports when you need a concise update, and drill into task detail when needed. You stay in control while the platform handles coordination at a scale that is hard to manage by hand.

Board + timelineReports + exportsTask drill-down
agent-fleet/projects/{projectId}/board
Project board showing work moving across stages, making agent activity visible and manageable at the program level.
Step 3A — See the whole program in motion

Board-level visibility makes it clear what is running, what is blocked, and where the fleet needs a human decision.

Project board
agent-fleet/projects/{projectId}/timeline
Project timeline with tasks grouped by feature and scheduled across queued, active, and completed states.
Step 3B — Plan execution timing

The timeline shows scheduled starts, active run windows, and completed milestones grouped by feature or agent, so teams can plan work instead of reacting to it.

Project timeline
agent-fleet/tasks/{taskId}
Task detail view with execution trace and outputs, showing how teams can inspect one assignment without losing the broader workflow context.
Step 3C — Drill into the trace

When you need detail, task-level history and execution context make every delegated step inspectable instead of opaque.

Task detail
Economics & governance

Cost control is built into the operating model.

J5 Agent Fleet does not treat spend as a back-office afterthought. Teams can review budgets, attribute usage by agent/model/project, and keep AI economics visible in the same workspace where work is planned, delegated, and reviewed.

Visibility across execution, accountability, and economics
Budget controls for new work before overages compound
Truthful cost attribution tied to the same operational workspace
The J5 Agent Fleet costs dashboard showing budget policies, spend attribution by agent, model, and project, and rolling spend windows alongside live execution.
Budget policies

Set limits before agent spend becomes a surprise.

Create budget guardrails at the right scope, review current usage, and see remaining headroom in plain language instead of hunting through billing tools.

Attribution

Trace spend by agent, model, and project.

Switch between operational views to understand which specialists, models, and projects are driving cost so finance and engineering can act on the same data.

Rolling visibility

Watch spend windows alongside live execution.

Daily spend trends, rolling windows, and active budget status keep economics visible while the fleet is running, not after the invoice lands.

Clarity

What J5 is not

Most teams evaluating J5 have tried other AI tools first. Here’s what sets it apart from the categories you already know.

Not a chatbot

J5 doesn't just answer questions. It structures work into projects, plans, tasks, and operating views teams can actually supervise.

Not a single-agent assistant

One generalist can't cover engineering, design, QA, marketing, and operations simultaneously. J5 coordinates a fleet of specialists, each with a defined role and scope.

Not a black box

Project chat, boards, timelines, task traces, and activity history keep execution visible. Teams can inspect what happened, what is scheduled, and what still needs review.

Not a prompt scrapbook

J5 manages projects, tasks, reusable bookmarked work, recurring jobs, budgets, and execution context — not just a library of saved prompts.

Not all-or-nothing automation

J5 is built for supervised autonomy. Teams can review plans, intervene at checkpoints, expand the roster when needed, and optionally add local project knowledge without pretending everything should run unattended.

What it is

An operations workspace for coordinating a fleet of specialized AI agents across real projects — with structured plans, project consultation, reusable workflows, timelines, custom specialists, per-agent budget governance, and a complete audit trail. Built for teams that need AI to operate with accountability, not just answer questions.

Problems we solve

Why existing AI tools fall short for serious work

Chat-based AI is powerful for quick answers. For structured, multi-agent execution at team scale, teams consistently hit the same walls.

Without J5

You paste the same project brief into five different AI windows and still can't tell what's been done or what's next.

With J5

One persistent project workspace where every agent works from the same context, brief, history, and consultation thread.

Without J5

AI produces output but you can't see what it did, why it made a decision, or whether the work is actually complete.

With J5

Live task boards, consultation states, step-level audit trails, and task detail views make every action traceable and reviewable.

Without J5

Useful work disappears after one run, so teams keep recreating the same prompts, task setups, and recurring jobs.

With J5

Bookmarked tasks and recurring work preserve repeatable execution patterns so teams can rerun proven work without rebuilding it from scratch.

Without J5

Even when AI work finishes, you still end up hand-writing status updates from scattered task traces, chat logs, and screenshots.

With J5

Day, week, and month reports turn real execution into concise markdown summaries with PDF-ready output, so stakeholders get the story without losing the evidence.

Without J5

You write individual prompts to delegate every task, which defeats the point of having autonomous AI.

With J5

Describe the outcome once. J5 decomposes it into a structured plan and routes work to the right specialists with the project context attached.

Without J5

A single generic assistant handles everything but excels at nothing — especially across engineering, design, QA, and operations.

With J5

A fleet of specialists across engineering, design, product, marketing, testing, and operations, plus the ability to add custom roles when the work changes.

Without J5

Everything runs right now, so you can't stage work for later or see how a full initiative will unfold across the team.

With J5

Project timelines and task scheduling make queued, active, and completed work visible by feature or by agent, so teams can plan execution windows before work starts.

Reporting & review

Turn live execution into a stakeholder-ready story.

J5 Agent Fleet does not leave teams stitching together updates from task traces and chat logs. Reports summarize a day, week, or month of work into a concise narrative with throughput, cost, and leverage already framed.

Weekly report

What shipped, what it cost, and what changed

Markdown + PDF-ready
Scope: last 7 daysSource: live fleet activity

What moved forward

Project chat and timeline updates shipped alongside reusable workflow clean-up and a refreshed marketing story.

Execution health

3 active initiatives, 11 completed tasks, 2 queued follow-ups, and no failed runs needing escalation.

Economics

$214 model spend this week with enough completed work to replace an estimated 31–40 hours of manual coordination.

Copy for docsReuse in slidesSend as recap

Period summaries

Generate day, week, or month recaps from live work.

Reports turn the current platform state into a concise narrative of what moved forward, what stayed blocked, and what is still in motion.

Shareable output

Use markdown now, hand off PDF-ready output later.

Teams can copy a report into slides, email, or docs immediately, then keep the polished export tied to the same execution record.

Operational context

Keep cost, speed, and leverage in the same story.

A useful update needs more than raw logs. J5 brings together shipped work, execution pace, spend, and human-time comparison in one place.

How it’s built

Precision, visibility, and governance at every layer

J5 isn’t a thin wrapper around a model API. Every part of the system is designed for the operational realities of running AI at team scale — with the controls ambitious teams require.

Goal-to-task decomposition

Describe an outcome in plain English. J5 structures it into epics, features, user stories, and executable tasks so work starts immediately rather than accumulating in a planning backlog.

Specialized agent routing

Tasks are matched to the right specialist — engineering work to engineers, design to designers, QA to testers, and so on — with the project context they need attached.

Project consultation in context

Project chat stays grounded in the brief, current plan, and task outputs. Teams can ask follow-up questions or review decisions without switching to a separate, context-poor thread.

Reusable bookmarked and recurring work

Useful task patterns do not have to disappear after one run. Teams can preserve repeatable work as bookmarks or recurring jobs and keep that activity visible alongside live execution.

Timeline scheduling and workload visibility

Project timelines show scheduled starts, active run windows, and completed milestones by feature or assigned agent, making future work as visible as live work.

Custom fleet expansion

When the work changes, teams can add new specialists with their own role, category, model, and operating instructions instead of forcing every task through a fixed roster.

Context-rich project intake

Projects can start with repositories, attachments, working-directory context, GitHub access, and executive summaries from prior work so planning begins with the real environment attached.

Operational reports and exports

Reports summarize a day, week, or month of execution in markdown with throughput, cost, and leverage context, then keep the PDF-ready handoff tied to the same underlying work.

Budget governance with hard limits

Set spending limits at any scope — global, per project, or per agent. Hard limits halt execution before a threshold is exceeded so AI costs never outpace your approval.

Full cost attribution

Every dollar of AI spend is tracked and attributed by agent, project, model, and task. Monthly dashboards and rolling windows give complete financial visibility — no surprises.

Complete audit trail

Every action, decision, and output is logged and attributable. Nothing happens silently. Everything is reviewable after the fact so teams can demonstrate what was done and why.

FAQ

Answers for teams moving beyond chat-based AI.

The questions below cover the core operating model: how J5 differs from generic assistants, how teams keep consultation, scheduling, reporting, reusable workflows, and cost visible, and what governance looks like as autonomous work scales.

J5 Agent Fleet is an operations workspace for coordinating specialized AI agents across real projects. It helps teams turn goals into structured execution with planning, delegation, live tracking, reusable workflows, and traceable outcomes.

A single assistant can help with one conversation at a time. J5 Agent Fleet is designed for coordinated execution across multiple agents, tasks, and workflows, with project structure, context management, reusable task patterns, and operational visibility built in.

Yes. J5 Agent Fleet is built for supervised autonomy. You can review plans, inspect task detail, monitor progress, pause or resume execution, and use consultation checkpoints where humans review work before it advances.

It is built for technical founders, engineering leaders, product teams, and AI-native operators who want to scale execution across complex work without losing visibility or control.

Yes. Project chat is seeded with the live brief, task descriptions, and task outputs from the current plan. That makes it easier to ask about risks, shipped work, or next steps inside the project instead of starting a fresh chat thread.

Yes. Teams can expand the fleet by creating their own specialists with a role, category, model, and operating instructions that fit the work they actually need to run.

Yes. J5 supports bookmarked tasks and recurring work so teams can preserve useful task patterns, rerun repeatable jobs, and keep that work visible in the same operating views as one-off execution.

Yes. Tasks can run immediately or at a scheduled date and time. Scheduled work stays visible in the same operating views as active work, which makes it easier to plan batch runs and keep humans aligned before execution starts.

Yes. J5 can generate day, week, and month reports from live platform activity, with concise markdown output for docs or slides and PDF-ready handoff when you need a polished recap.

The project timeline visualizes tasks on a Gantt-style view. Teams can group by feature to follow delivery milestones or by assigned agent to inspect workload, with scheduled starts, run windows, and completion points visible in one place.

Optionally, yes. For projects with a valid local workspace, J5 can maintain project-scoped QMD knowledge and show configuration status directly in the product. It is an operational aid for grounded project context, not a claim of universal memory.

The costs workspace gives teams rolling spend visibility, budget policies, and hard-stop guardrails for new work. You can see spend before it compounds and intervene with clear operational context instead of reacting after the billing cycle closes.

Yes. J5 surfaces spend and usage across multiple views so teams can inspect economics by task history, agent, model, and project. That makes it easier to spot where paid usage is concentrating and adjust operating choices before costs drift.

J5 keeps planning context, task history, outputs, and operational activity attached to the work. That gives teams a concrete trail for reviews, compliance conversations, and post-mortems instead of relying on scattered chat logs.

Teams typically start with one real project, connect the relevant repositories and context, and let J5 decompose the work into an operational plan. From there, they can expand the roster with specialized agents while keeping humans in the review loop.

Autonomous systems only perform well when they understand the work environment. J5 Agent Fleet lets teams reuse prior project context, connect repositories, preserve decisions, maintain project-scoped knowledge when needed, and chat against the live plan so agents can act with better judgment and less repetition.

Approval gates are human checkpoints that block agent execution until a team member explicitly signs off. They are useful before high-risk actions, external-facing changes, spend-heavy tasks, or any step where a human decision is genuinely required. Gates can be configured by checkpoint type, risk level, or task type, and the platform keeps a full audit trail of who approved what and when.

Yes. The agent runner daemon lets you connect any Mac, Linux, or Windows machine as a local execution node. Download the binary for your platform, generate a one-time install token in Settings → Runners, and run the one-line install command. The daemon registers itself as a background service and starts polling for assigned tasks. Agents then run with full access to your local repositories, CLI tools, and environment.

J5 Agent Fleet offers a free Trial to get started, a Free tier with a monthly task allowance, a Pro tier for individual power users, and a Team tier for collaborative workspaces. See the Pricing page for current limits. Paid plans are billed through Stripe and can be managed from Settings → Billing at any time.

Yes. The Free tier includes a monthly task allowance so you can run real work without a credit card. When you reach the limit you can upgrade to Pro or Team from Settings → Billing. Trial accounts also get an extended window to explore the full feature set before choosing a plan.

Early access

Be first to coordinate your AI workforce.

J5 Agent Fleet is in early access. Join the waitlist and we’ll reach out to discuss how it fits your team’s work.

0/500

No spam, ever. We’ll only reach out about J5 Agent Fleet access.