Bring your own AI.
SalesLobe governs it.

Your agent decides what to say. SalesLobe decides whether it has earned the right to send, with an audit trail of every decision. Connect any AI system to the SalesLobe API and every message it writes goes through the same governance layer as a human rep.

Available on Pro and Agency plans.

A prompt governs nothing.

Anyone can wire an LLM to an inbox. The hard part is everything around it: who approved this message, does it stay within the client's tone, what happens when the model gets it wrong, and can you prove, later, who wrote what. A raw agent has no gate, no trail, and no way to earn trust. That's not an AI problem. It's a governance problem.

The governed loop.

01

A reply comes in

Your workspace receives the reply. SalesLobe fires a signed webhook (lead.replied) to your endpoint, and if Corty analyzed it, also a second event (corty.suggested) with Corty's draft, confidence score, and classification. Both include the reply_id your agent needs.

02

Your AI decides

Use Corty's draft as context, write its own reply, or skip. Your agent, your logic, your models. SalesLobe doesn't care what your AI is built with.

03

It submits the send

POST /v1/replies/{reply_id}/send with the message body. One endpoint, one API key, scoped to exactly what your agent needs.

04

The governance gate decides

No active autonomy grant? The message does not send. It's stored as a pending draft in the review queue, visible in the dashboard and waiting for a human. With earned autonomy, it sends immediately. Either way, the decision is logged.

This response is the product.

The first time your agent calls the send endpoint, this is what it gets back:

HTTP 202. Accepted, not sent. Your agent's draft is in the review queue; a human approves, edits, or rejects it in the dashboard. Nothing your AI writes reaches a prospect until it has earned that right. Handle 202 as success with pending, not as an error: it means the governance layer is doing its job.

POST /v1/replies/:id/send
202 queued_for_review
{
  "status": "queued_for_review",
  "reply_id": "dd235c7e-…",
  "reason": "no_active_autonomy_grant"
}

Agent Control Plane · Earned Autonomy

Your agent doesn't get a shortcut. It earns autonomy exactly like your best rep did.

No separate rulebook for AI. Corty, your human reps, and your own agent all climb the same L0 → L3 ladder, earn autonomy the same way, and can be pulled back to zero the same way. No exceptions, no bypass.

Teams are wiring LLMs to inboxes and campaigns faster than they can govern them. A raw agent with send access has no gate and no track record. That's not an AI problem, it's a governance problem.

So every external agent starts at Level 0: all sends queue for human approval. As its drafts prove out, approved unchanged and aligned with your tone rules, the org owner grants it more autonomy, until approved sends go out immediately. Pull it back to zero at any moment.

How Earned Autonomy works

Human. Agent. Corty. Same ladder.

L3 Full autonomy
Thomas · rep L3 · earned, not assigned
L2 Guided autonomy
Corty L2 · 94% aligned
L1 Selective review
Your agent L1 · 0% aligned · climbing
L0 Full review
← agents start here

Positions are earned per actor: any of them can reach L3, and any of them can be pulled back to L0.

Agentic AI is outrunning governance

Teams already ship custom agents to their inboxes and campaigns. A raw LLM with send access is a compliance risk waiting to happen, not a feature.

One control plane, every actor

Nobody manages trust agent-by-agent or rep-by-rep. Every actor proves itself on the same ladder, so autonomy means the same thing everywhere.

Built for the rules already coming

The EU AI Act's transparency obligations start landing in August 2026. Provenance recorded at the moment of sending, not detected after the fact.

Every decision, on the record.

Each send attempt, queued or sent, is written to an append-only decision log: which actor (your agent, identified by its API key), whether a grant was active, what action resulted, and when. If your agent edited Corty's suggestion, the edit distance is recorded too. The full chain is visible per reply in the dashboard as a Decision Trail: suggested, submitted, queued, approved, sent, each step with its actor and timestamp.

We don't detect AI-written text after the fact. We record it at the source.

Provenance is becoming the requirement.

The EU AI Act's transparency obligations begin applying in August 2026, and the direction is clear: organizations deploying AI that interacts with people will increasingly need to show when and how AI was involved. You can't retrofit that onto sent email; AI-written text carries no watermark, and detection tools are unreliable. What holds up is provenance recorded at the source: who drafted, who edited, who approved, who sent. That's what the decision log gives you, per message, from day one.

SalesLobe provides an audit trail, not legal advice; how the AI Act applies to your use case is a question for your counsel.

Alignment

Corty learns from your agent, too.

Pass original_suggestion and your agent's final text with the send, and SalesLobe measures the distance between what Corty proposed and what your agent decided. Over time that becomes a signal: an agent whose edits shrink is converging on the workspace's voice, the same alignment evidence a human rep produces, and the same basis for earning autonomy. Two models, one governance layer, one score.

Corty
suggests
Agent
decides
edit distance → alignment signal

BYOK

Whose AI, whose bill.

Running Corty on your own key (BYOK)

Corty's classification and drafting can run on your own Anthropic API key. You pay inference directly, and the key is encrypted and never exposed. Available on Pro plans and above.

Connecting your own agent

Your agent runs on whatever stack you choose, on your own infrastructure and your own model bills. SalesLobe never sees its internals. You use the API, and Neural Credits cover the platform and governance layer.

Pricing

Metered, not mysterious.

A full pipeline run (classification, Corty's draft, governed send) is 1 Neural Credit. Sends where your agent brings its own text are metered separately; that pricing is being finalized during the partner pilot. Webhook delivery and read requests are not charged.

Connect in an afternoon.

1

Create an API key in your workspace

Scope it to only what the agent needs: leads.read, replies.send, webhooks.manage. Don't use a full-access key for an agent.

2

Register your webhook endpoint

POST /v1/webhooks, then verify the HMAC signature on incoming events.

3

Handle the events

lead.replied and corty.suggested. Fetch the full reply via GET /v1/replies/:id when you need more than the truncated preview.

4

Send via the API

POST /v1/replies/:id/send, and treat 202 queued_for_review as success.

5

Build a track record

Your first sends land in the review queue. Approve them in the dashboard, build a track record, earn autonomy.

What we're building next.

Direct Gmail and Outlook send integration, so governed autonomy extends to day-to-day inbox replies. And we're exploring, with our pilot partners, native connectors so agents and assistants can discover and use SalesLobe without writing HTTP: same governance, less plumbing. If you're building in this direction, we want to hear from you.

Apply for the partner pilot

You don't need to apply to start building. The API docs are open, and Level 0 (reviewed sending) works with any Pro API key today. The pilot is for teams ready to earn autonomy.

Common questions

What if our agent sends something wrong?
At Level 0 it can't send at all: every submission is queued for human review. Autonomy is granted only on demonstrated alignment, and can be revoked instantly. The gate is enforced in the API, not in documentation.
What if our agent submits something that violates our tone rules?
Without autonomy, it never reaches a prospect: every submission is queued for human review, and that review is where your rules are enforced today. Alignment with your tone guides is also exactly what determines whether an agent earns autonomy in the first place, and autonomy is revocable the moment it drifts. Automated tone checks on agent submissions are on our roadmap (see: spot check autonomy).
Do you have an MCP server or SDK?
Not yet. Today it's a documented REST API with webhooks, which is deliberately the simplest thing to build against. Native connectors are on the roadmap with our pilot partners.
Which AI can we connect?
Any system that can receive a webhook and make an HTTP call. SalesLobe is model-agnostic about your agent: governance applies to what it submits, not to how it thinks.
What exactly gets logged?
Every send attempt: the acting API key, whether an autonomy grant was active, the resulting action (queued or sent), timestamps, and, when you provide Corty's original suggestion alongside your agent's text, the edit distance between them. The chain is visible per reply as a Decision Trail.
How does our agent get autonomy?
The org owner grants it, based on the agent's review track record. During the partner pilot we work through this together, so apply via the contact page.
Does this replace Corty?
No. Corty keeps classifying and suggesting (unless you turn suggestions off), and it learns from your agent's edits the same way it learns from human edits. Most partners use Corty's draft as context for their own agent.

Your AI is ready.
Make it accountable.

Connect it this week: first sends reviewed, autonomy earned, every decision on the record.