All work/Aether Labs

AI research tools / 2023

Aether Labs.

04 / 06

Less searching. More discovering.

Industry
AI research tools
Platform
AI web application
Our role
AI · Engineering
Project year
2023
01 / The product at a glanceIllustrative product interface

[01] — The overview

A little context.
A bigger picture.

An AI workbench for research teams working across documents, questions and ideas. Aether Labs brings document ingestion, retrieval-augmented search and agent workflows into a single research environment.

Designed for
Research teams & knowledge workers
The core journey
Collect → ask → investigate

[02] — The thinking

The challenge

Make a growing body of research usable.

Research is rarely contained in a single document. The product challenge is helping teams move through a collection of material, ask useful questions and keep the connection between a response and the source information.

The approach

Keep the evidence in the workflow.

The workbench is organised around a connected research loop: bring in documents, search the collection and investigate relevant material. Retrieval and agent interactions sit alongside the source context so the interface supports active research.

[03] — The experience

Thought through.
From end to end.

01

Document workspace

An organised home for research material, with document ingestion as the starting point for discovery.

02

RAG-powered search

Natural-language questions connect with relevant material from the document collection.

03

Agent workflows

Repeatable research tasks have a place in the workbench, with the workflow and its context visible to the team.

02 / A closer look at the experience · Illustrative interface

One connected journey

  1. 01

    Collect

    Bring research material together.

  2. 02

    Ask

    Explore a focused question.

  3. 03

    Inspect

    Return to relevant source material.

  4. 04

    Continue

    Build on the research thread.

[04] — The details

The scope behind
the screens.

Design & delivery scope

  • Research workspace architecture
  • Document ingestion experience
  • Conversational search interface
  • Source-context interaction patterns
  • Agent workflow UI
  • System-state & feedback patterns

Areas of focus

  • AI
  • RAG
  • Agents

Product notes expand on the project brief. They describe the experience and its design direction.

Behind the interface

Design and engineering considerations.

Visible source context

Relevant documents should remain close to the research question and its response.

Understandable AI states

Processing, retrieval and response states help people understand what the workbench is doing.

A useful feedback loop

Research workflows benefit from clear ways to refine a question and inspect a result.

[ The product ambition ]

Bring the research question and the source material closer together.

The aim is an AI workspace that helps researchers navigate their knowledge and continue investigating with context.

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