Technical support has spent decades getting better at handling problems. The next era is about eliminating them. Founded by AI PhDs, Mosaic AI is helping support teams get there first.
For years, support teams got faster at answering, better search, routing, and macros. Then AI made faster answers ubiquitous.
But technical support was never really about answering faster. It’s about finding the root cause, in products where every install is configured differently and the same symptom means something different for every customer.
Without it, the AI simply guesses confidently and moves on, leaving your best support engineers to check its work. The same cases just keep coming back, and cost to serve never moves.
We built Mosaic AI to fix that
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We believe technical support is moving through three waves. Most teams are somewhere between the first two today. Mosaic AI is building for all three.
Every case, log, and conversation is recorded and connected, so nothing your team learns gets lost.
Mosaic AI investigates alongside your team, connecting the customer’s setup, product behavior, and past cases to find the cause. You get the evidence to fix the issue and help others facing the same problem.
The product and the customer talk directly. Problems are caught before they become cases, and support is measured on what it prevents, not what it absorbs.
Mosaic AI was founded by AI PhDs and NLP professors whose research focuses on complex reasoning for question answering. That's the same problem technical support teams face every day: reasoning across configurations, logs, and product terms to find what's actually wrong.
combined AI research experience
of our team holds advanced degrees in AI and ML
published including 3 papers cited over 30 times
building enterprise support systems
Led AI gamification efforts at the Allen Institute for AI, and has authored over 20 scholarly articles and multiple patents in AI and NLP fields. Previously founded the software startup BlueTail, which was acquired by Salesforce.
Lead research at the Allen Institute for AI on AI agents for scientific discovery. Awarded the Azrieli Early Career Faculty Fellowship which is given to eight scientists across all fields of study.
Computer science professor of machine learning and natural language processing. Studies center around understanding and mapping natural language to programs.
CS Phd candidate in Natural Language Processing. Specialize in complex reasoning, multi-hop question answering or reasoning over multiple modalities.
Research focuses on agentic RAG, agent memory, and how AI support agents learn from human corrections. Research paper accepted to EMNLP 2026 as the top 5% of submissions.
A diagnosis is only useful if you know when to trust it. Every part of Mosaic AI is built to earn that trust.
Human review by default, with confidence thresholds you set.
See how we do it with Triage →
We’re building toward product-led support, where problems are caught before they become cases.
See how the Platform works →
Every resolved case becomes knowledge that prevents the next one.
See how we do it with Knowledge →
A dedicated AI research team works alongside yours from pilot to full deployment.
When Mosaic AI isn't sure, it says so and flags the case for a person instead of guessing.
Our team brings together AI researchers, engineers, and people who've worked in support themselves. What we share is a drive to find out why.
We share context freely, bring the right people in early, and capture what we learn, so every project starts further ahead than the last.
We come with strong opinions but are happy to be proven wrong, letting the evidence settle debates.
We'd rather dig into a messy, unsolved problem than polish an easy one.
Tel Aviv and Toronto, working as one. We make time to connect beyond the work, from biweekly happy hours to yoga and cultural events in Tel Aviv.
See open roles →
“We have been able to scale and keep up with the demands without having to add a significant amount of headcount. With basically the same size team we had last year, we’ve made improvements.”
“We see plenty of opportunities where it’s going to help us streamline our customer interactions and make us more efficient and effective.”
Mosaic AI runs every support workflow on one shared framework: Agent Builder plus the Customer Context Model, connected to your stack once.
Learn more
We analyze your real case data, at no cost, to find where time, effort, and spend accumulate, what can be automated, and how much it would lower your cost to serve.
You get a live environment built for your top use cases, running on your own systems, using your own case history. You see the result before you sign anything.
Deployed on top of Salesforce, Zendesk, and the rest of your stack. No migration, no developer resources, deployment expertise included.
We’ll analyze a sample of your real cases, identify where Mosaic can have the greatest impact, and show how it would work in your current support stack.
