For event platform teams

Ship AI features without derailing your roadmap

Your customers are asking for AI: lead scoring, matchmaking, sponsor reports, event summaries. Your engineers are busy keeping the platform running. Toobler builds those features alongside your team, using data your platform already collects, with a person approving anything important before it reaches a customer.

Prioritize your AI backlog

Your roadmap is full. Your customers want AI anyway.

  1. 01 — The current state

    Most event-tech engineering teams spend their week on maintenance and on features that were promised months ago. Meanwhile, customers keep asking for AI assistants, sponsor performance reports, exhibitor lead insights, matchmaking, better analytics and deeper CRM integrations. Every one of those requests competes for the same engineers.

  2. 02 — How Toobler engages

    We take the AI, data and integration work off your core team's plate. We work as part of your engineering team, bring experience of how event data actually behaves, and build each feature into your existing platform. You own what we build, and you aren't tied to us to keep it running.

  3. 03 — What changes

    AI requests stop being an open-ended risk on the roadmap and become scoped pieces of work with a clear plan. Your core team keeps its focus on the platform, and every AI feature ships with review built in from day one.

What we build

What's in scope for AI feature development

The features event-tech companies ask for most.

  1. Lead scoring AI for sponsors and exhibitors

    Rank leads using badge scans, booth visits and session attendance, so exhibitors know who to follow up with first.

  2. Matchmaking AI for attendees and exhibitors

    Suggest who should meet whom based on session interests, past meetings and profile details, inside your own platform.

  3. Event AI integration across your stack

    Connect AI features to the registration, CRM, badge-scanning and reporting systems you already run. Nothing gets ripped out and replaced.

  4. AI governance and human review

    Anything that reaches a customer or updates a CRM record goes to a person for approval first, with a record of what was approved and the data behind it. We use Zahen, our governed AI platform, for this step.

  5. Tested before release

    We test each feature against realistic event data, including messy registrations and incomplete session records, before your customers see it.

  6. Sponsor and exhibitor reporting

    Turn booth, session and engagement data into reports that show sponsors and exhibitors what they got from the event.

How an AI feature gets from your data to your customers

Every feature follows the same five steps.

  1. 01

    Connect your data

    Pull registration, session, badge-scan, sponsor and CRM data from the systems where it lives today.

  2. 02

    Map to a common event data model

    Bring data from different sources into one consistent structure, so a feature behaves the same across all your products.

  3. 03

    Generate the output

    Produce the lead scores, matches, sponsor summaries or post-event reports.

  4. 04

    Human approval via Zahen

    Anything that matters goes to a person for sign-off before it is published, and the decision is logged.

  5. 05

    Publish and sync

    Approved results appear in your platform or sync to your CRM, and the audit log is kept.

How we work together

Start with a sprint, then keep building

What's included in the AI feature sprint?
A short, fixed-scope piece of work. We map your AI backlog, your data sources and the gaps in your integrations, then give you an architecture and a pilot plan for the features that matter most, such as lead scoring, matchmaking or sponsor reporting.
How does this fit around our core roadmap?
We take the AI, data and integration work, so your core team can stay on the platform roadmap.
What happens after the initial sprint?
You can keep working with us on AI features, on event data and CRM integration, or with a dedicated engineering pod that delivers continuously alongside your team.
Do you replace our platform or our team?
No. We work inside your existing team and stack. You get more engineering capacity and people who know event platforms, not a new platform.

Built by engineers who know event platforms

Toobler has spent years building production event technology for a global events business: attendee experience, networking and meetings, sponsors and exhibitors, onsite operations and mobile. That is why we understand event data well enough to build lead scoring, matchmaking and reporting that work in production, not just in a demo.

We are an engineering partner, not a product vendor. We build AI features and integrations into the platform you already run.

The AI drafts. A person approves. The record is kept.

Event Technology

More across the event stack

Other ways we help event-tech teams build, connect and modernize their platforms.

See the full Event Technology overview

Ready to prioritize your AI feature backlog?

Start with a fixed-scope sprint. We'll map your AI backlog, data sources and integration gaps, and give you an architecture and a pilot plan you can act on.

Prioritize your AI feature backlog

Related

Frequently asked

What AI features can be added to an event technology platform?
The most common are lead scoring for sponsors and exhibitors, matchmaking for attendees and exhibitors, sponsor and exhibitor performance reports, CRM sync and post-event summaries. Each is built on the registration, session, badge-scan and CRM data your platform already produces.
How does lead scoring AI work for event platforms?
It ranks leads using signals your platform already captures, such as badge scans, booth visits and session attendance. The data is mapped into one consistent model and checked for quality before the feature goes live, so exhibitors can trust the ranking.
What is matchmaking AI for event technology platforms?
It suggests which attendees, sponsors and exhibitors should meet, based on session interests, past meetings and profile details. We build it as a feature inside your existing platform, not as a separate product.
How is AI governance handled for event-tech features?
Anything the AI produces that reaches a customer or writes to a CRM record goes to a person for approval first, through Zahen, our governed AI platform. Nothing is published automatically, and each decision is logged.
How does event AI integration work with our existing stack?
We connect AI features to the systems you already run, such as registration, badge scanning, CRM and reporting, through defined data mappings and sync points. You don't need to replace your platform or add a separate system.

Start with one measurable use case.

A Readiness Sprint is a fixed-scope engagement that maps your integration and AI readiness and produces a production-oriented plan — before anything is built.

Book a Readiness Sprint Schedule a Call