Case study 01 · Built at Aether
See how Aether
builds working systems.
Event Scout finds relevant business events, filters for fit, scores opportunities, verifies details, and organizes ready-to-review lists.
Real problems. Working systems.
Event Scout · Interactive demonstration
Search
Filter
Score
Verify
Export
The problem
Finding and evaluating relevant events required too much manual research.
The system
Event Scout searches, filters, scores, verifies, and organizes opportunities — turning a manual research chore into a short, ranked list ready for review. Built and used internally at Aether AI: not a paying-client engagement, but a real, working system running on real events.
The outcome
Faster event research, consistent scoring, easier review, and one place to manage opportunities.
In-house case study
From scattered event listings to a reviewable opportunity pipeline.
Aether built Event Scout for its own event research. The system brings discovery, filtering, scoring, verification, and export into one workflow, so a person can review the shortlist instead of starting from a collection of browser tabs.
A consistent shortlist
Each discovered event is evaluated against defined criteria rather than judged from memory. The workflow makes relevance easier to review and compare.
Verification before action
A verification stage checks the details before the export. People retain responsibility for deciding which opportunities to pursue.
One place to review
Dashboard and pipeline views bring event leads, fit scores, and outreach readiness together instead of leaving findings scattered across tabs and notes.
What this demonstrates
The actual dashboard and pipeline screenshots below show the working interface. This is Aether’s internal project, not a client engagement. Screenshots document the product; they do not establish a time-saving percentage or revenue result.
Measuring effectiveness
A timed manual-versus-agent comparison has not yet been published. The next evaluation should compare research time, verified relevant events, and corrections needed for the same brief.
Problem
Finding and evaluating relevant events required too much manual research.
Solution
Event Scout searches, filters, scores, verifies, and organizes opportunities — turning a manual research chore into a short, ranked list ready for review. Built and used internally at Aether AI: not a paying-client engagement, but a real, working system running on real events.
Architecture
A scheduled agent run pulls listings from public event platforms, normalizes them into a common structure, and passes them through a filtering and scoring pass before writing results to a reviewable export.
Workflow
Outcome
Faster event research, consistent scoring, easier review, and one place to manage opportunities.
Before / After
Before
- Check multiple listing platforms by hand, on a recurring basis
- Judge relevance case-by-case, from memory
- No consistent scoring — every event gets re-evaluated from scratch
- Findings scattered across tabs and notes
After
- One scheduled agent run checks every platform automatically
- Every event filtered against the same defined target profile
- Consistent, repeatable scoring on what's left
- One reviewable, ranked export to work from
Technology
Screenshots
Dashboard — running totals and the pipeline at a glance.
Pipeline — every discovered event, scored and filterable by territory.
Demo
Demo in progress
A walkthrough of this project isn't recorded yet — check back soon.
Lessons
- Filtering criteria has to be explicit and specific — vague relevance rules produce noisy shortlists.
- Verification before export matters more than raw recall; a smaller, trustworthy list beats a long uncertain one.
Potential Business Applications
- Local businesses scouting sponsorship, sampling, or brand-partnership opportunities
- Sales teams identifying in-person events to work
- Marketing teams building an events calendar without manual research