Launch HN: Risely (YC S25) – AI Agents for Universities
Higher ed is full of inefficiencies. Every department runs on outdated systems that don’t talk to each other. Today, advising staff are looking up enrollment data in PeopleSoft or Ellucian, checking grades and assignments in Canvas, and trying to track engagement in a CRM, if they even have one. Often, it’s just spreadsheets and email. One advisor told us they were losing 8+ hours/week just trying to answer: “Which students are struggling?”. During that lag, students slip through the cracks, and every lost student costs a school tuition.
I’ve spent the last decade building large-scale systems, but about a year ago, I left my job to build something personal. My time at UC Berkeley reinforced what my parents taught me when we immigrated to the U.S. - that education is the most powerful tool for upward mobility. But nearly 40% of students never graduate. Many of these students are capable and just need support, but the systems meant to support them are overwhelmed and broken.
So we built Risely. Our first agent focuses on academic advising and retention. It connects to a school’s systems, unifies the data, flags at-risk students, drafts outreach, and answers natural-language questions about caseloads and course progress. It gives staff leverage and time back, while helping more students stay on track.
The harder part is everything under the hood: - Connecting to archaic SIS, LMS, and CRM systems with inconsistent APIs and data models - Normalizing messy institutional data into something agents can reason over - Handling real policy constraints around FERPA, isolating tenant data, and meeting strict security and privacy standards for student PII - Designing agent workflows that are traceable, reviewable, and safe to run in production - Building infrastructure that can adapt to different institutional rules, processes, and edge cases.
We started with advising because retention ties directly to both revenue and student success. But the same foundation applies to registrar, admissions, financial aid, research administration, and other critical functions. As more agents come online, they can begin to coordinate with each other and hopefully improve the entire operations of a college or university.
If you’ve built systems that had to reconcile messy data, inconsistent workflows, or policy constraints using LLMs, we’d love to hear how you approached it.
We’d love to hear your thoughts about the above, and anything in this space!
Where those systems are more closed, we work with the institution to find creative but still sanctioned paths such as through their integration hub or data warehouse. That way we are not asking the vendor for special access, just making better use of the plumbing that is already there.
We should talk. I used to work with universities.
- Integration tax: Each module still lives in its own data model. Schools end up exporting CSVs or building Mule pipelines to reconcile SIS+LMS+CRM. Our agent sits on top of all sources with pre-built connectors and a unified schema, so coaches see enrollment + Canvas grades + attendance in one call (like in the Triage Center)
- Operational burden: Products like Data Cloud or Agentforce are powerful but need admin capacity that smaller schools just don’t have. We ship a default ruleset for advisors + prompt library so an advisor can be productive immediately.
- Cost creep: Several platforms meter GPT usage or require new AI licenses. We price per active student so budgeting is predictable, which is a big plus for universities and their unique budget cycles.
Curious if you’ve found pain points around data normalization especially (this is the hard, very custom part of our work right now). Happy to keep the discussion here for the benefit of others, and if you’d like to dive deeper my email is sadia@risely.ai
I know a few different companies who ultimately moved out of the education market completely or just try to leverage their education traction as a beachhead to other markets. It sounds like you're focused on the education market - what's your take?
Staff and administrators are also just people working in critical functions. When the tools help with their day-to-day job functions, the willingness to adopt is there. We’ve stayed focused on education because the problems are tied directly to retention and student success, and those are outcomes schools care deeply about.
We're a small non-profit liberal arts school, and we already have 70+ integrations feeding to and from the various sources of truth and systems of record. It's a mess.
We intend to be an interoperable layer that sits on top of these systems, and allows users to not only surface valuable insights but also take actions within those systems in a secure and compliant way. You can think of it less as reporting and more as a “system of work” that leverages LLMs and agents to streamline the messy, cross-system tasks that slow people down today.
Are you hiring? I have 8 years of university SIS implementation & migration experience and 2 years of Edtech AI engineering experience and this is the exact problem space I want to work in.
Would love to chat! Feel free to reach us at hiring@risely.ai
I do think you have value in pulling in the disparate data sources and using LLMs to present the data in a clean way to the advisor/user.
We've found the "chat" functionality to be especially useful for advisors since we've been able to surface insights to them without them having to log onto many different systems and just present it in a clean output, as you pointed out.