Platform · Build · The pipeline

Agentic Teams

One chatbot degrades the moment the questions span specialties — and the usual fix makes a person the router, hand-carrying context between AI tools that forget each other. An Agentic Team is one conversation backed by a roster of specialists: an orchestrator routes each message by intent, the session state travels through every handoff, and the whole exchange runs under one scope and one trace.

Compose your first team Start from a template
At a glance
  • Interfaceone chat · real-time voice
  • Made ofspecialist agents
  • Routingper message, by intent
  • Contextshared, checkpointed state
  • Per agentKBs · tools · R/C/U/D
  • Governance4 scopes · cost + runtime caps
  • Every turntraced & costed
IN A SOLUTION PACK

In a pack, a team arrives assembled: specialists, intent routing, and scoped access already configured.

See Solution Packs →
app.turtlecoworker.com/teams/editor
The team editor: team identity, routing instructions and governance settings on the left, the docked roster of specialist agents with their capability chips on the right
The team editor: identity, routing and guardrails on the left, the specialist roster docked on the right.
Why it's built this way

When the human is the router,
the context is the casualty.

A generalist assistant is shallow on your specifics. A drawer of separate bots forces someone — an agent on your team, or worse, your customer — to know which one to open and to re-explain everything at every switch.Context dies at each boundary, and the boundaries multiply.

A team removes the boundaries instead of the specialists. The orchestrator reads each message and hands it to the agent that owns that intent, over shared session state that survives every handoff. To the person talking, it feels like one expert who happens to know everything.

Why teams switch

Most AI gives you one generalist chatbot that's shallow on your specifics, or a pile of separate bots with a human routing between them. A team is one conversation backed by specialists: every message routed by intent, with the context intact at every handoff.

What most AI tools give you
  • One generalist assistant that's vague on your tools, data and policy
  • Or separate bots, with a person deciding which one owns each question
  • Context lost at every switch: the customer re-explains, the thread restarts
  • No say over what any of them can actually touch
What Turtle AI Coworker gives you
  • One chat — or a live voice line — backed by a roster of specialists
  • Each message routed by intent to the agent that owns it
  • Checkpointed session state: handoffs keep the whole conversation
  • Every specialist scoped to its own tools, knowledge and data
Time to configure
~20 min
Compose agents you already built and write the routing rules. No canvas to wire.
Cost per message
~$0.03
You pay for the tokens each reply uses; the router adds only a light classify step.
Effort to operate
Routes itself
Every message finds its specialist automatically; policy-held writes still wait for approval.
See it work

Ten chats, each routed for you.

One conversation, mixed intents. Watch how each message finds its specialist, and how the topic changes mid-chat without anyone picking a bot.

A customer asks a billing question, then reports a bug, then asks how to export a report, all in one chat, each needing a different expert.

01Billing first

“Why was I charged twice?” routes to the billing specialist, which reads the account table and explains.

02Then a bug

“The export button is broken.” The router switches to the technical specialist, which checks known issues in its KB.

03Then a how-to

“How do I export to CSV?” goes to the how-to specialist. Same conversation throughout.

3 experts
the customer never noticed they talked to three: the routing is invisible.
How it's wired

Where a team gets its answers.

Behind the one conversation, each specialist links to the same substrate: your knowledge, your data, your tools, your models. Every turn is governed and traced.

Talk to it in
In-app chatWebsite widgetSlackMicrosoft TeamsAPI / SDK
Your Agentic Team
the team · one accountable run
Router · reads each message's intentroutes to →
BillingTechnicalHow-toPolicyDataActions

Ask about one thing, then another. Each message goes to the specialist that owns that intent, in the same conversation.

reads & writes, permission by permission
Governance · wraps every run
Permissions decide what it can touchApproval gates hold risky writes for a humanBudgets cap spend per runA full audit trace records every step
Anatomy of a team

A router, a roster, shared state, one gate.

Seven properties that turn several narrow agents into one deep coworker — without giving up control of any of them.

01 · Routing

Intent routing replaces the human switchboard.

When AI tools multiply, a person becomes the router: read the message, decide which bot owns it, paste the context across. Here the orchestrator does that job. Routing lives in a prompt — one rule per specialist, phrased by kind of request — which the system compiles into a structured execution plan the supervisor follows deterministically at run time. Changing how work flows is editing a sentence, not re-wiring a diagram.

  • One routing rule per specialist, phrased by kind of request
  • Compiled into a structured execution plan the supervisor executes
  • A default agent for ambiguous requests, and a named final reviewer
The team editor's instructions panel: the orchestrator routing prompt with one rule per specialist, and the generated execution plan shown alongside
Routing as prose, executed as a plan
02 · Roster

Specialists stay narrow, so answers stay deep.

A generalist model asked to cover billing, debugging and policy is shallow at all three. A team keeps each specialist narrow and grounded: its own instructions, its own knowledge bases, its own tools, its own table permissions, its own model. The roster rail shows every agent's full reach as chips — tables with R/W markers, knowledge, tools — so you audit the whole team without opening a single agent.

  • Each card shows Tables · Knowledge · Tools at a glance
  • Model per agent: cheap models for routine work, a stronger one for routing
  • Editing an agent here edits only its role on this team
The docked roster rail: one card per specialist agent showing its model, description, and Tables/Knowledge/Tools chips with R/W markers
The roster: every specialist's reach, visible as chips
03 · Shared state

Context survives every handoff.

The failure mode of juggling separate AI tools is that context dies at each boundary — the customer re-explains, the thread restarts. A team runs one conversation over shared, checkpointed session state: when the router hands a message from the billing specialist to the technical specialist, the new agent arrives knowing everything the conversation already established. Follow-up messages resume from the checkpoint, not from zero.

  • One session, checkpointed: state persists across turns and handoffs
  • A specialist receives the conversation, not a pasted summary
  • Session history and memory carry across the whole exchange
A team chat session where the conversation moves between two specialists mid-thread, with the earlier context visibly carried into the second agent's answer
A topic switch mid-chat: the context comes along
04 · Scoping

Every specialist is scoped in four deliberate steps.

Composing agents multiplies reach, so scoping is a first-class step, not a checkbox. A four-step wizard walks each agent's capability surfaces in order — details, knowledge, tools, table access — and table access means four independent permissions per table, Read / Create / Update / Delete, enforced at run time. Least-privilege is the default: only Read starts on.

  • Step 1–4: details · knowledge bases · tools · table access
  • Per-table R / C / U / D, enforced by the runtime, Delete off by default
  • Put the delivery tool on one agent; keep reference tables read-only
Step 4 of the agent wizard: the per-table Read / Create / Update / Delete toggle pills, with a target table granted R+C+U and a reference table read-only
The security step: four toggles per table, per agent
05 · Voice

The same team, on a real-time voice line.

A routed team isn't limited to text. Teams run on a real-time voice stack built on production media infrastructure: streaming speech-to-text, voice-activity detection, noise cancellation, and low-latency speech synthesis, so a caller talks to the team the way they'd talk to a person. The routing underneath is unchanged — each utterance still reaches the specialist that owns it, under the same scope and the same trace.

  • Streaming STT and low-latency TTS over live media transport
  • Voice-activity detection and noise cancellation built in
  • Same routing, same permissions, same audit trail as text
shot: teams-voice-sessionA live voice session with a team: the active call view showing live transcription streaming and the responding specialist indicated
A conversation, spoken: the routing works the same
06 · Governance

Governed from the layer, not the honor system.

A team is several agents acting as one worker, so the governance layer treats it as one worker. A circuit breaker can be scoped to the team itself — trip thresholds on error rate or cost that pause the whole team, not just one specialist. Every tool call any specialist makes crosses the same policy engine, policy-held writes wait for a single-use human approval, and the workspace budget caps what the team's runs can spend.

  • Circuit breakers scoped to the team: one trip pauses every specialist
  • Every specialist's calls governed by the policy engine; held writes go to approvals
  • Workspace budget caps cover team runs like any other spend
The Compliance page's circuit-breaker view: a breaker config targeting an Agentic Team, with its error-rate and cost thresholds and recent trip events
One worker to govern, however many agents inside
07 · Trace

One conversation, one trace — handoffs included.

When work hops between tools, accountability hops with it and usually gets lost. Here every turn of a team conversation lands in one activity trail: which agent was invoked, every tool call it made, every handoff between specialists, with per-message token counts and cost. Replaying any past session — who asked, what routed where, what ran, what it cost — is a lookup, not an archaeology project.

  • Activity events per turn: agent start/end, tool calls, handoffs
  • Per-message tokens, duration and cost, aggregated per session and team
  • Config versioning: each run pinned to the team configuration it ran under
A session's activity trail: the sequence of routed agents with handoff events, expandable tool calls, and per-message cost figures
The whole conversation, replayable: routes, calls, cost
One conversation, worked

A support chat for a SaaS company, message by message.

A scenario: a SaaS company puts its customer-facing support chat on a team — a billing specialist, a technical specialist, an escalation specialist, one router. Here is what the system does with one real conversation. No human routed anything.

Message
“Why was I charged twice this month?”
The orchestrator classifies the intent and dispatches to the billing specialist — the only agent with read access to the billing table. It finds the duplicate charge and explains it, citing the two line items. The route and the reads land in the trace.
Switch
“Also, exports have been failing since Monday.”
A new intent, mid-conversation. The router hands off to the technical specialist, which arrives with the full session state — it already knows who the customer is and what was just discussed — and checks the known-issues knowledge base. Nobody re-explained anything.
Escalate
“This cost me a client. I want a refund.”
The router recognizes an escalation and dispatches the escalation specialist. It drafts the make-good — and the refund, an external write, is held by policy at the approval gate. A support lead approves once; the grant is single-use.
Resume
The customer replies the next morning
The conversation resumes from its checkpoint: same session, same context, same specialists. The follow-up routes to whoever owns it, with yesterday's exchange intact. On the voice channel, the same conversation happens spoken — streaming transcription in, low-latency speech out.
Record
The whole thread is one trail
Every turn is recorded: which specialist was routed, each handoff, every tool call with sanitized payloads, per-message tokens and cost — pinned to the team configuration in force at the time. When someone asks what the AI told this customer and who approved the refund, the answer is a lookup.
A support session's trace: three routed specialists across one conversation, a handoff event, a held refund write showing its approval decision, and per-turn cost
One conversation: three specialists, one handoff trail, one held write
What you can build

If one outcome spans several skills, it's a team.

Customer support chat

Billing, technical and escalation specialists behind one customer-facing conversation.

Internal IT + HR desk

One chat for every internal question, routed to the runbook or the handbook specialist.

Doer + reviewer

One agent drafts the work; a separate reviewer agent checks it before anything commits.

Compliance triage

Classify an incoming item, route by risk, draft a response, and hold every write for review.

Data-source router

A broad-read router answers cross-cutting questions by dispatching to per-source specialists.

Parse → decide → notify

A multi-stage pipeline where each stage is its own auditable agent; only the last one posts.

The payoff
1
conversation, however many specialists it takes — routing is the system's job, not a person's.
0
context lost at a handoff: shared, checkpointed session state travels with every route.
4
per-table permissions per specialist, defaulting to least-privilege: only Read on.
100%
of turns traced and costed: every route, handoff and tool call on one trail.
From the live catalog

Built on Agentic Teams.

All templates
Website Sales Concierge
Agentic Team · Sales

A customer-facing pre-sales chat team for your website. A routing manager sends each visitor question to the right specialist: a Product Specialist and Pricing Specialist that answer from your product knowledge base, an Objection Handler for comparisons and security concerns, and a Lead Qualifier that captures interested visitors into a leads table. Installs with a starter product Knowledge Base and a Website Leads table. Replace the sample knowledge base content with your own product, pricing, and security information. Grounded in the knowledge base, with no invented claims.

4 specialistsrouting
Official · ~15 min
Product Launch War Room
Agentic Team · Marketing

A cross-functional launch team that turns a product update into a coordinated go-to-market kit: positioning, channel content, and competitive framing. A supervisor routes among a messaging lead, a channel content lead, and a competitive analyst.

3 specialistshierarchical
Official · ~15 min
Sales Engine Pro: Deal Desk (Internal)
Agentic Team · Sales

Internal, rep-facing companion team for the Sales Engine Pro pack. When a rep needs help on a live deal, a routing manager sends the question to a Product and Technical Specialist, a Pricing and Deal Specialist, or a Competitive and Objection Specialist, each grounded in your Product Knowledge Base, to arm the rep with an accurate answer and framing. Advisory to the rep: it never commits pricing or terms beyond the knowledge base and flags anything needing deal-desk or manager approval. Pairs with the customer-facing Website Sales Concierge. Install alongside the Sales Engine Pro pack. Requires an LLM provider. Replace the sample product knowledge base with your own.

3 specialistsrouting
Official · ~10 min
Live Call Co-pilot
Agentic Team · Sales

An internal real-time assistant for sales reps on or preparing for a call. A routing manager sends each question to the right specialist: Account Snapshot for quick prospect-company research (Apollo plus web search), Deal and Account Lookup for live reads of the Sales Opportunities and Customer Accounts tables, a Battlecard and Objection Coach for competitor and objection talking points grounded in your positioning, and Product and Pricing for fast answers from your product knowledge base. Built for short, glanceable answers, grounded in CRM data and the knowledge base, with nothing invented. Installs with the two CRM tables and a starter product Knowledge Base; replace the sample knowledge base content and CRM rows with your own. Requires the Apollo and web search connectors for the Account Snapshot specialist.

4 specialistsrouting
Official · ~15 min
Employee Engagement Team
Agentic Team · Sales

Run surveys, plan events, and generate engagement reports

3 specialistshierarchical
Official · ~8 min
Patient Access Pod
Agentic Team · Healthcare

A front-office coordination team that takes a new patient from intake to a booked, coverage-verified visit: clean intake with red-flag screening, urgency triage support, appointment scheduling, and an eligibility/prior-auth check: all as drafts and guidance for clinical and staff approval.

4 specialistshierarchical
Official
Questions

The details, up front.

Why not just use one capable generalist assistant?
Because depth doesn't survive breadth. One prompt covering billing rules, debugging procedure and escalation policy is mediocre at all three, and gets worse with every specialty you add. A team keeps each specialist's instructions, knowledge and access narrow — which is also what your security review wants, since a billing agent that can't touch the ticketing tool is a smaller blast radius than one assistant wired to everything.
How does routing actually work — is it a workflow canvas?
No canvas. Routing is written as a prompt — one rule per specialist, by kind of request — and the system compiles it into a structured execution plan the supervisor follows at run time. The team supports routing, hierarchical, sequential and collaborative orchestration modes. Changing how work flows is editing a sentence, and every routing decision is visible in the trace.
What happens to context when the topic changes mid-conversation?
It carries. The conversation runs over shared, checkpointed session state: when a message routes to a different specialist, that agent receives the full conversation context, and a follow-up message tomorrow resumes from the same checkpoint. The customer never re-explains, and no human copies context between tools.
Can customers talk to a team by voice?
Yes. Teams run on a real-time voice stack — streaming speech-to-text, voice-activity detection, noise cancellation and low-latency synthesis over live media transport — so a caller holds a natural spoken conversation. Routing, permissions and the audit trail work identically to text; voice is a channel, not a different system.
How is a team kept from doing something it shouldn't?
In layers. Each specialist has its own least-privilege scope: its tools, read-only knowledge, and per-table Read / Create / Update / Delete enforced at run time. The team carries one autonomy scope and hard cost and runtime ceilings per run. And every tool call from any specialist crosses the platform policy engine — a held write waits at the approval gate for a single-use grant, whatever agent proposed it.
What does a past conversation look like to an auditor?
One trail. Every turn records which agent was routed, every tool call with sanitized inputs and outputs, every handoff, and per-message token counts and cost — pinned to the immutable team configuration in force at the time. Session and team-level cost roll-ups come from the same records.
Next rung on the ladder

A team runs a pipeline. An employee owns the role.

AI Employees