AI-powered artist validation & matching

Hitting the right note with a marketplace platform gets incredibly difficult when your backstage operations can’t keep up with the headline act. That was the reality for GigPig, the UK's largest live music marketplace, powering 50,000 gigs a year and channeling £10 million into the artist economy. 

While their marketplace was booming, their growth was held back by a tedious, manual review process. Every single artist profile, from bio checks to YouTube link verifications, had to be audited by hand. With over 10,000 artists queuing up, this manual bottleneck was threatening to turn down the volume on their expansion. 

Miquido stepped in to orchestrate a seamless solution, building an AI-powered artist validation engine and an intelligent venue recommendation system in just four months. Integrated directly into GigPig's existing software stack, the upgrade collapsed artist onboarding time from a sluggish one hour to a crisp five minutes per profile. By automating the heavy lifting, the platform now clears the stage for rapid growth, saving over £250,000 annually in operational costs, without skipping a beat or adding to the headcount. 

01. Facing a manual validation growth

Every artist profile required human eyes to check images for appropriateness, review bios for quality, verify links, and validate genre selections. At a scale of 10,000+ artists, this process was creating severe backlogs and slowing down an artist's time-to-live.

02. Correcting profile discordance to protect recommendations

GigPig's venue-to-artist matching depends on profile data being complete, accurate and consistently structured. Incomplete or miscategorised profiles don't surface in the right searches. This means artists miss bookings they should have won, and venues see matches that don't fit their brief. Improving onboarding quality wasn't just an operational problem, but a commercial one.

03. Meeting venue demands for faster talent discovery

With thousands of venues looking for the perfect act, the matching equation was massive. Venue managers needed to filter through thousands of artists by genre, budget, and real-time availability to make lightning-fast booking decisions. 

04. Demanding an integration with zero backstage disruption

GigPig’s platform relied on a mature, stable architecture running daily. Introducing advanced AI capabilities couldn't mean rebuilding core systems from scratch or introducing parallel infrastructure risks. 

01. Embedding AI seamlessly into the existing arrangement

Miquido used a proprietary LLM operations framework to integrate generative AI directly into GigPig’s existing codebase. This lightweight architecture handles safety checks and output consistency, allowing internal teams to manage it effortlessly.

02. Engineering an automated AI artist validation engine

Our team built an intelligent validation engine that automatically audits profiles, checking image relevance, Youtube links attribution, assessing bio tone, and cross-checking profile tiers. The system automatically drafts feedback messages for the artists, handling 90% of onboarding autonomously.

03. Composing an embedding-based recommendation engine

We built a smart filtering and ranking engine that surfaces at least 30 ideal artist matches per venue search. The system scores similarities across genres and budgets, even generating AI explanations so venue managers know exactly why an artist fits the bill.

01. Setting a record tempo for artist onboarding

Reviewing a profile now takes just five minutes instead of an hour—a staggering 92% time reduction. Artists go live almost instantly, backlogs have evaporated, and internal teams are freed up for high-value tasks.

02. Trimming the operational fat out of the mix

The AI validation engine saves approximately 150 hours of manual review work every month. This reduction is the equivalent of adding significant team capacity without adding operational headcount.

03. Striking a highly profitable chord for the bottom line

Eliminating manual moderation directly translates to over £250,000 in annual savings, drastically improving unit economics as artist volume and gig bookings scale across the UK.

04. Accelerating the entire marketplace harmony

The journey from profile submission to live booking availability is now 75% faster. This velocity translates directly to more matches, more bookings, and more revenue flowing straight into the live music ecosystem. 

05. Creating a future-proof artificial intelligence foundation

The integration gives GigPig a robust foundation for continued automated development without complex architectural rebuilds. The system was engineered to scale with the platform seamlessly over time.