AI strategy that ships.

We help mid-market companies build bespoke AI solutions to solve their biggest problems while protecting their data.

We're the team behind Topia Interactive and SchoolSpace.io, powering millions of hours of virtual campus, multiplayer learning, and classroom infrastructure.

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From roadmap to rollout.

AI Readiness & Strategy

We assess your data, infrastructure, and team to build a realistic AI roadmap tied to business outcomes, not buzzwords.

Solution Design & Implementation

From selecting the right models to integrating them into existing workflows, we build AI solutions your team can actually use.

Enablement & Scale

Training, change management, and ongoing optimization so AI doesn't just launch. It lasts.

Why Topia Consulting

Built by builders.

Our team comes from ERP development and custom software shops. We built a spatial computing platform that now serves as a virtual campus, classroom, and multiplayer learning system with 150,000+ students each year across the country. AWS Partner since 2023. We deliver K12 Zone, a white-label deployment of the Topia technology, for Stride (NYSE: LRN) within their AWS infrastructure. Nominated for Product Hunt's Product of the Year in 2021 alongside Oculus Quest 2. Was host of the 2020 Official Virtual Burning Man.

Leadership

Daniel Liebeskind

Daniel Liebeskind

CEO

LinkedIn →

Banker and private equity operator turned software engineer. Daniel built the development shop behind Topia from the ground up — from first prototype to a platform serving 150,000+ students. His superpower is sitting in the gap between business complexity and technical execution: understanding the nuances of your business and building solutions to your biggest problems.

Christopher Psiaki

Christopher Psiaki

CTO

LinkedIn →

Twelve years as an ERP developer and co-inventor of a programming language for bespoke enterprise systems. Chris then architected Topia's patented peer-to-peer spatial engine — the real-time infrastructure that powers millions of hours of live interaction in the browser. When your problem requires deep systems thinking and technology that doesn't exist yet, Chris builds it.

Danielle Diamond

Danielle Diamond

Head of Product

LinkedIn →

Built Topia's Product and Customer Success organizations from scratch. Former Lehman Brothers and Barclays analyst across equity research and fixed income. Adjunct professor at Stanford teaching product design. Danielle bridges what customers actually need with what teams can deliver — and makes sure the whole machine runs after launch.

AWS·Stride (NYSE: LRN)·Burning Man·Adobe·Okta·Stanford·Yale·Ubisoft

The hard truths about AI.

Why Topia Consulting instead of a Big 4 firm?

We are software engineers and product builders who have scaled real infrastructure. We don't deliver 100-page theoretical slide decks; we deliver functional roadmaps and production-ready platforms.

How do you keep sensitive data secure?

If you're using AI today, your data is flowing through infrastructure you don't control. That's fine for some data. It's not fine for all of it.

We set up a routing system that matches each type of data to the right inference destination: on-premise, private cloud, public cloud, or public AI APIs. The architecture follows the data, not the other way around.

Highly sensitive data (financials, customer PII, medical records, proprietary processes) should never be sent to a public AI provider. We make sure it doesn't have to be.

Should we be building agents?

Yes, and the window to get ahead is open right now. An agent has an LLM brain, a prompt, and tools. Agents automate work, give your people superpowers, and surface business intelligence that wasn't possible before. The question isn't whether agents will run inside most companies. They will. The question is whether yours will be ready.

To get the most out of agents, you need a context graph: every data point, process, customer relationship, and decision pulled into a structured knowledge layer your agents can use. Without it, your agents are guessing. With it, they're informed.

The right approach is hybrid. Sensitive data gets inferenced on hardware you control. Frontier models run inside Bedrock or Foundry. The architecture follows the data. The agents follow the architecture. We help you build both.

Do we need to rebuild all our SaaS tools?

No. Not now, and maybe not ever for some of them. Keep using Salesforce, HubSpot, your ERP. They're sources of truth and they do their jobs.

What you need to start doing is syncing your data out of them into a secure context graph that will power AI agents across your organization. When vendors restrict API access, or when AI makes it trivial to rebuild their tools, you want to already have your data. Sync first. Rebuild when the time is right.

If I'm already on an enterprise plan of Claude or ChatGPT, isn't my data protected?

Somewhat. They won't train on your data, but it's still flowing through their infrastructure, processed by their systems, subject to their terms of service and security posture.

More importantly, your context graph is accumulating in their system, not yours. That's the asset that matters. Enterprise privacy terms don't change who owns it.

Stop waiting. Start building.

No pitch deck. No pressure. Just a 30-minute conversation about what's possible for your business.

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