Most gig platforms store listings. bndy is building a continuously learning model of grassroots live music.
We call the intelligence layer behind it BNDY Backline.
A local gig might appear on a venue website, a social post, a listings site, a poster, an artist's own page, or be sent directly to bndy by someone who knows it's happening.
That someone might be the artist, the venue, a gig-goer or a BNDY Curator who knows their local scene because they're part of it.
Those sources can disagree. They can change. They can disappear.
Most systems copy the latest thing they found into a database and quietly lose the story behind it.
Backline keeps the evidence.
It remembers what each source said, when it said it, and how strongly that source should be trusted for that particular fact.
AI is useful for messy information, ambiguous names, posters and relationships. But the model itself is not treated as truth.
The original evidence stays underneath the decision.
If one source says a gig starts at 9pm and another says 9:30pm, we don't have to throw either one away.
Backline can retain both claims, their sources and their timestamps, then decide which is better supported.
Backline breaks what it sees into small assertions: this artist has this name, this venue is at this address, this gig is on this date.
That makes provenance, disagreement and later correction first-class parts of the system.
Better evidence can arrive tomorrow. Backline does not need to rewrite history to accept it.
The evidence stays. The resolution changes. The public view can then change with it.
Traditional software wants an ID or an error. Real life is messier.
If two artists might be the same act, Backline can keep that uncertainty, gather more evidence and resolve it later instead of inventing certainty.
Automated discovery can search further and faster. It still doesn't know a local scene the way the people in it do.
A gig sent to bndy by a user, artist or venue matters. So does something found and added by a BNDY Curator who is actually out there going to gigs and helping their local scene get seen.
Technology gives BNDY scale. People give it local knowledge.
It is the current product view of what BNDY believes.
The durable evidence underneath it is what lets that belief be challenged, explained and improved.
This is the technical bit. You were warned.
The useful question is not only "what is connected to what?" It is also "who says this is true, what evidence supports it, and what conflicts with it?"
That makes Backline closer to an epistemic graph: entities and relationships plus the evidence behind them.
Backline is not designed around the assumption that automated discovery is inherently better evidence.
Community submissions, artists, venues and BNDY Curators can all contribute observations. Their provenance can travel with the fact just like a website, feed or captured poster.
An AI agent can follow relationships, inspect observations, seek corroborating sources and leave an identity unresolved when the evidence is weak.
The aim is agentic reasoning over durable knowledge, not an LLM writing directly into production tables.
The public Artist, Venue and Event records stay fast and simple for the app.
Backline sits underneath them, preserving the richer evidence and reasoning needed to rebuild or revise that view safely.
Connected evidence is a better substrate for multi-step questions than flat text chunks alone.
A future graph projection can support GraphRAG-style traversal without making a graph database the source of truth.
Backline is built as a low-cost serverless runtime rather than an always-on crawler farm.
The graph is currently a derived view over durable evidence and claims. A dedicated graph store may come later if it earns its place.
Once artists, venues, gigs and sources are connected over time, BNDY can begin to see patterns that individual listings cannot show.
Where live music is growing. Which venues are becoming more active. Where scenes connect. Where activity is disappearing. Which sources are reliable. Which parts of grassroots music are missing from conventional commercial datasets.
And some of that picture will come from the people who know these scenes because they are actually in them: artists, venues, gig-goers and BNDY Curators helping local music get found.
We are trying to make the scene easier to see, understand and support.
Still with us? Respect.
Now go and use all that technology for its actual purpose: finding a gig.
Open the map. See the live music around you tonight, tomorrow, this weekend. Walkable, a short drive, somewhere worth going.
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