Introducing Auron

Auron turns real conversations into durable, queryable intelligence, without depending on ad hoc note-taking or whoever happened to write the best summary. It is built on the observation that spoken interactions carry the richest context there is: intent, constraints, implicit requirements, risk, and the reasoning behind a decision. Auron captures that and converts it into structured outputs that can be governed, audited and fed into the systems you already run.

The problem

In most organizations the important context appears in conversation, and then scatters. Decisions get buried in email threads. Requirements discussed in a meeting never reach the tracker. Two people remember the same commitment differently. The cost shows up later as rework, missed commitments and a customer explaining something for the third time.

Auron replaces that with a repeatable pipeline: conversations become evidence, intelligence is extracted as structured output, durable context accumulates on the record, and follow-through is triggered under configurable control.

How it works

A conversation enters. An agent joins a meeting or a call under a defined operating mode, or you type to it in a chat, or you upload a transcript of something that happened elsewhere.

It becomes evidence. A time-coded transcript and its session metadata form the primary record. Everything downstream points back at it, which is what makes the outputs defensible rather than merely plausible.

Intelligence is extracted. Structured summaries, and signals: the decisions, requirements, risks and commitments that matter in your context. Each signal keeps the quote it came from.

Shared context is updated. Signals and validated observations update the record's context and the organization's memory, with provenance. The next conversation about that account starts from what the last one established, and preparation stops being archaeology.

Follow-through is triggered. Automations run around the session and can pause to ask a person before acting. Where execution belongs in your own systems, Auron passes the context and lets them run it. That separation keeps Auron focused on intelligence rather than becoming another workflow engine you have to migrate to.

The concepts

Delivered as assistants

Auron is a platform, and it usually reaches people as an assistant aimed at a job. Assistants share the same machinery and differ in domain focus, signal catalog and where follow-through goes.

An assistant is one or more agents with a defined persona and posture, a domain signal configuration, scoped knowledge, controlled integrations where tool access is needed, and the governance bindings to go with them. Teams typically start with one, learn how it behaves, and expand from there. See Creating an agent.

Built for enterprises

Auron is for organizations that want to build and run their own agents with real control over identity, access, safety boundaries and evidence. It emphasises governance and integration flexibility rather than embedding a workflow engine you then have to adopt.

Everything is organization-scoped. An agent, a conversation, a record, a knowledge store, a signal, a toolkit, an action outcome: each is created and governed inside the boundary of one organization, and that boundary is what tenant isolation and access enforcement are built on. See Organizations.

For customers with elevated requirements, Auron can be deployed into a customer-specific environment so data, credentials and operational controls are fully isolated. See Security.

Two ways in

The web console is where an organization is configured and read. The mobile app is where the work happens away from a desk. Both run against the same organization, and each does the half it is suited to.