Empowering B2B Teams to Rank Higher & Get Cited With AI-Native Agentic Workflows

Approach

Replaced brand onboarding forms with a conversation the system can learn from

Before eminnt writes anything, it learns the company. We designed the knowledge base as a guided conversation rather than a form, so the answers arrive already in the shape the system needs.

It holds how a company describes itself, who it sells to, what it offers and how it sounds. Each area settles once complete, giving everything downstream a stable foundation to build on.

It also records what the company would never say. Holding those boundaries as explicitly as the preferences is what keeps a voice consistent across hundreds of pieces.

Turned the expert interview into an agentic questionnaire that writes its own next question

Case studies stall because the people who did the work rarely have time to write it up. We inverted the task, so instead of a document waiting to be filled, the system interviews them.

Questions arrive in the order a person would naturally ask them, and a checklist fills in as the conversation moves. Anything already known is skipped, and the conversation can be left and resumed without loss.

The same answers then produce the finished pieces. Proof that existed only in someone’s memory becomes something the company can send.

Emi's personality, her judgement, and the guardrails she works inside

Emi runs the workflow, deciding which agent picks up the work and when. She is direct and willing to hold an opinion, leading with whatever matters most. Difficult results are stated plainly, neither softened into meaninglessness nor made dramatic.

Most of the character is restraint. She does not confirm work before checking it, does not begin writing without a clear instruction, and where a rule could be replaced by removing a capability, it was.

Connected the work to its results, so Emi knows where you stand

Most content tools stop at publishing, leaving results in one place and the work in another. We connected them, so every published piece carries its own performance back into the system.

Emi reads that as a position rather than a dashboard: what is on pace, what has slipped, and what sits close enough to be worth returning to. Improvement continues the original work instead of starting over.

One rule holds underneath it. The system writes the sentence and never the number, so the account of how things are going is calculated before it is phrased.