AI Solutionsat Berkeley
Berkeley tech consultants who build, not just advise.
You bring it. We build it.
Bring a bottleneck or an AI idea your team hasn’t had bandwidth for. A cross-functional Berkeley student team, including EECS and Haas talent, scopes the work, puts together a deck or recommendation, builds a tailored solution, product, or piece of software, and hands it over.
- 2026
- UC Berkeley
- 8–11 weeks
Beyond the Deck.We go further.
Most AI advice stops at a recommendation. The hard part, making it work on your data and inside your workflow, is left with you.
We don't just prescribe the medicine. We help provide the treatment.
The deck isn't the product. The solution is.
- Which problem is worth automating first?
- What can your data support?
- What happens when the model is wrong, and can you live with it?
What we can do.
Four kinds of work. Bring the one that matches the problem on your desk.
- Discover the problemExample: market research, mapping a process end to end to find where the hours go, and ranking what AI should, and shouldn’t, touch.
- AutomateExample: classify and route inbound requests, draft first replies, and escalate anything below a confidence threshold to a person.
- SystemsExample: an internal Q&A or copilot over your docs, with retrieval and evaluation so answers stay grounded.
- IntegrateExample: a scoped prototype or feature wired into tools you already use, handed over with documentation.
Each project is scoped to one of these. We’d rather finish one scope well than four halfway.
How a project works.
An 8–11 week engagement with a team of 5–8 Berkeley students, including a project manager. We scope carefully, then build, test, and hand over.
- Weeks 1–2ScopingStakeholder interviews and a written problem statement. If we can’t state the success metric in one sentence, we haven’t scoped it yet.
- Weeks 3–7BuildingSprints with partner check-ins. Something demoable exists mid-engagement, whatever else is still in motion.
- Weeks 8–9TestingHeld-out checks, a plain record of how it fails, and cost and speed under realistic use.
- Weeks 10–11HandoffDocumentation, an implementation handoff, and a candid note on what we’d do with more time — as the project needs.
Why AIS.
We bring together students across engineering, data science, business, design, and research to tackle problems from multiple angles.
- Strategy through execution. We don’t stop at recommendations. Our teams can research the market, identify opportunities, build and test AI solutions, and deliver something your team can actually use.
- Built for experimentation. AIS gives companies additional bandwidth to explore ideas, prototype faster, and test projects that internal teams may not have the time or resources to pursue.
- Cross-functional by design. Each project combines technical and business talent so what we build is not only technically possible, but useful, practical, and aligned with how your organization operates.
Business · AI/ML · Data · Engineering · Product · Design · Strategy
Our Team
Eight founding members across engineering, product, operations and marketing. Curious about joining? See Students for how we recruit.
What an engagement leaves you with.
Typically these four. What each one turns out to be follows the problem.
Bring us a challenge — even if you’re not sure what the solution should be. A specific bottleneck, a backlog idea, or an AI question your team hasn’t had time to explore.
A working prototype or tool
Evaluation findings
Documentation
Implementation handoff
Think of us as a low-risk testing ground. An engagement is a contained way to find out whether an AI idea holds up against your own data and your own workflow, before it needs headcount, a vendor contract, or a place on the roadmap.
What we ask for is a real scope, a point of contact who can answer questions inside a week, and access to whatever data the work requires.
Strong first projects are often sitting in someone’s backlog: a manual process nobody has measured, a pile of unstructured documents, a support queue, an internal tool that never got built. Startups, research groups, campus units and non-profits are all welcome.
- Confidentiality
- We'll sign your NDA. Anything not cleared for publication stays out of our public write-ups.
Berkeley students
Want to build AI with a cross-functional team? See how we recruit and follow us for the next cycle.
