You're right, incumbent SIS/LMS vendors are rolling out AI features. We’ve studied (and, in my past life at Salesforce, helped build) some of them. What we keep hearing from IT teams is:
- 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
The key issue for the sector is the tens of legacy systems that don't integrate with each other, often with manual spreadsheet processes that could be easily automated. Yet the big players like Oracle sell a generic CRM experience that doesn't fit well with higher education.
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.
Completely agreed, that is one of the biggest challenges in this industry! And it's surprising how many software systems are being used by higher education that aren't designed or built for them.
Would love to chat! Feel free to reach us at hiring@risely.ai
How's it like working with schools/universities as a startup? I've always heard edtech can be a slow, bureaucratic sales cycle (and maybe not a high willingness to pay?).
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?
That was one of our assumptions too, since you often hear about long cycles and low willingness to pay. Once we started gathering feedback and learning about the pain points, we found a strong appetite for technology that makes jobs easier and more effective.
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.
Impressive and a good mission startup!
How did you get workday, peoplesoft etc. to give the data to you? I assume all these companies do not like to share data, since as someone else also pointed out that each of these system of records are adding AI capabilities and bundling them.
Appreciate the kind words. You’re right that the big SIS and ERP vendors are building their own AI features, but at the end of the day institutions own their data and expect interoperability across systems. Workday, PeopleSoft, and similar systems all provide APIs or integration layers that schools already use for reporting and warehousing.
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.
The recommendations don't look very insightful, and seem like a rephrasing/summary of the alert above it. For example the first student who has account holds, bad grades, etc. the recommendation is just to schedule a meeting. I don't think the LLM will be able to provide super insightful recommendations. Even in the improvement plan generated by the agent, the steps seemed pretty generic(as expected from LLMs).
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.
That is great feedback, and agreed that LLMs definitely have generic outputs, especially if missing the right context. To combat this, we're actively working on playing with which data we can pull, how to cleanly give it to an LLM and which models to use to improve the inference (while staying within the compliance boundaries).
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.
Very cool work. I particularly like your focus on student outcomes and building a curriculum that extends beyond the classroom to extracurriculars. I hope you succeeed.
Thank you, appreciate the support! Our goal is to ultimately get this in the hands of staff AND students, who expect to be using good technology with intuitive user experiences so that student outcomes improve not only in the classroom but across the full student experience.
Sounds like a massive band aid. What do you do when that band aid is no longer maintained properly? You wouldn't be able to rebuild the systems underneath because the staff are now reliant on interfacing with the band aid.
Wouldn't it have been a better long term fix to replace the antiquated systems?
Would love to chat! We are always looking to gain insight on how we can improve our product with existing data, and this sounds like a great input. Feel free to reach us at founders@risely.ai
I'm 10+ years into IT in higher ed. I'm intrigued by the ideas here. Do you envision Risely being entirely a reporting system that runs _against_ existing systems and data, or do you envision Risely being another source of truth where some data lives? Because if it's the latter, I'm feeling big xkcd.com/927 feelings.
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.
I love that comic, and thank you for bringing it up because we are trying to avoid exactly that. We don't intend to be a system of record, we fully recognize that higher education has deep integrations with systems of record that contain complex business rules.
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.
All of those system of records are adding exactly those capabilities and bundling them at no extra cost. How do you plan on overcoming that?
We should talk. I used to work with universities.
You're right, incumbent SIS/LMS vendors are rolling out AI features. We’ve studied (and, in my past life at Salesforce, helped build) some of them. What we keep hearing from IT teams is:
- 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
The key issue for the sector is the tens of legacy systems that don't integrate with each other, often with manual spreadsheet processes that could be easily automated. Yet the big players like Oracle sell a generic CRM experience that doesn't fit well with higher education.
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.
Completely agreed, that is one of the biggest challenges in this industry! And it's surprising how many software systems are being used by higher education that aren't designed or built for them.
Would love to chat! Feel free to reach us at hiring@risely.ai
Thanks! I've emailed.
hi lancefit, you might be interested in looking at doowii.io as well. I'm the CEO, and you can email me at ben [at] doowii [dot] io
How's it like working with schools/universities as a startup? I've always heard edtech can be a slow, bureaucratic sales cycle (and maybe not a high willingness to pay?).
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?
That was one of our assumptions too, since you often hear about long cycles and low willingness to pay. Once we started gathering feedback and learning about the pain points, we found a strong appetite for technology that makes jobs easier and more effective.
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.
Impressive and a good mission startup! How did you get workday, peoplesoft etc. to give the data to you? I assume all these companies do not like to share data, since as someone else also pointed out that each of these system of records are adding AI capabilities and bundling them.
Appreciate the kind words. You’re right that the big SIS and ERP vendors are building their own AI features, but at the end of the day institutions own their data and expect interoperability across systems. Workday, PeopleSoft, and similar systems all provide APIs or integration layers that schools already use for reporting and warehousing.
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.
The recommendations don't look very insightful, and seem like a rephrasing/summary of the alert above it. For example the first student who has account holds, bad grades, etc. the recommendation is just to schedule a meeting. I don't think the LLM will be able to provide super insightful recommendations. Even in the improvement plan generated by the agent, the steps seemed pretty generic(as expected from LLMs).
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.
That is great feedback, and agreed that LLMs definitely have generic outputs, especially if missing the right context. To combat this, we're actively working on playing with which data we can pull, how to cleanly give it to an LLM and which models to use to improve the inference (while staying within the compliance boundaries).
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.
Very cool work. I particularly like your focus on student outcomes and building a curriculum that extends beyond the classroom to extracurriculars. I hope you succeeed.
Thank you, appreciate the support! Our goal is to ultimately get this in the hands of staff AND students, who expect to be using good technology with intuitive user experiences so that student outcomes improve not only in the classroom but across the full student experience.
Sounds like a massive band aid. What do you do when that band aid is no longer maintained properly? You wouldn't be able to rebuild the systems underneath because the staff are now reliant on interfacing with the band aid.
Wouldn't it have been a better long term fix to replace the antiquated systems?
We should chat. We rapidly capture the existing operating models in universities for analysis and optimization of administrative workflows.
Would love to chat! We are always looking to gain insight on how we can improve our product with existing data, and this sounds like a great input. Feel free to reach us at founders@risely.ai
I'm 10+ years into IT in higher ed. I'm intrigued by the ideas here. Do you envision Risely being entirely a reporting system that runs _against_ existing systems and data, or do you envision Risely being another source of truth where some data lives? Because if it's the latter, I'm feeling big xkcd.com/927 feelings.
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.
I love that comic, and thank you for bringing it up because we are trying to avoid exactly that. We don't intend to be a system of record, we fully recognize that higher education has deep integrations with systems of record that contain complex business rules.
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.