Education · Campus operations automation
Your admin team is answering questions the SIS already knows
Enrolment queries, fee reminders, timetabling clashes, and helpdesk tickets pile up because every response requires a staff member to look something up — in a system that already holds the answer.
Banao builds campus automation agents that read from your SIS, billing system, and timetabling engine, handle the routine query automatically, and escalate only what genuinely needs a human. Staff keep the judgement calls; the agent handles the lookup.
What a Banao campus automation deployment covers
We start with the query types that consume the most staff hours and work outward — not by deploying every feature at once.
Enrolment query agents
An agent wired into your SIS that answers deadline, document, and status queries over email, web chat, or WhatsApp — reducing the inbound queue without removing the staff who handle edge cases.
AI-assisted timetabling
Constraint analysis across rooms, staff availability, and course load to surface conflict-free slot options — so schedulers make decisions instead of checking spreadsheets.
Fee reminder and payment-chase automation
Multi-channel reminders triggered from your billing system at the right point in the payment cycle — no manual list-pulls, no missed chase dates.
Helpdesk ticket routing and auto-resolution
Incoming tickets classified by query type and either resolved automatically against your knowledge base or routed to the correct team with context already attached.
Admissions and enrolment document intake
Forms, transcripts, and supporting documents read and pushed into your SIS fields, with a human-review queue for anything the model is uncertain about.
Operations dashboard for admin heads
Query volume, resolution rate, and pending case age in one view — so operations managers see where the bottleneck is, not just that one exists.
We run our own operation on the same AI before you do
Banao operates a ~300-person engineering company using its own AI products. InterviewGod handles our own hire screening; Vikaas manages our own demand-generation pipeline. Every agent we propose for your campus has already had to survive our own back-office first.
That is not a sales point — it is the development discipline. A campus agent that fails on an unusual query in production will fail on ours first, and we fix it before it reaches your institution.
- InterviewGodScreens Banao's own engineering hires every week.
- VikaasRuns Banao's own demand-gen pipeline end to end.
When campus automation is not the right starting point
Some conditions make a campus agent harder to justify. We will tell you before you start:
- Undocumented SIS data: an agent reads what is in the system. If enrolment records are inconsistent or incomplete, automation surfaces the data quality problem — it does not solve it. Data remediation needs to come first.
- Highly variable processes: if admissions rules or timetabling constraints change every semester, an agent trained on last year's rules rots faster than it saves time. We map the variance before recommending automation.
- Low query volume: if the admin team fields fewer than a few hundred inbound queries a week, the overhead of maintaining an agent may exceed the hours saved. We will say so.
How we start — scope before build
We do not quote a campus agent from a requirements document. We audit your actual query types and SIS structure first.
- AI Discovery Sprint2 weeks · fixed price
We analyse a sample of your real inbound queries, map them to SIS data availability, and hand back a coverage estimate and a prioritised automation scope — yours to keep regardless of what you decide next. If you proceed, the Sprint cost is credited against the build.
- Build
Agent development, SIS and helpdesk integration, knowledge-base wiring, and a human-escalation path for queries the agent cannot resolve. Includes UAT with your admin team before go-live.
- Production and iteration
Live deployment with monitoring, an admin dashboard, and a monthly review cycle — so query coverage improves as your team logs the gaps the agent misses.
Frequently asked questions
Which student information systems do you integrate with?
We have integrated with SAP, Ellucian Banner, PeopleSoft Campus Solutions, Blackbaud, and several institution-built SIS platforms. The Discovery Sprint maps what your SIS exposes via API or structured data export and confirms what an agent can reliably read from it.
What happens when the agent cannot answer a query?
The agent hands off to a human with the original query and whatever context it retrieved — so the staff member picks up mid-way rather than starting from scratch. The failed query is logged for review, and common failure types feed into the next update cycle.
Can the agent handle multiple languages?
Yes. We deploy multilingual agents for institutions with diverse student populations. Language configuration is part of the build scope — we confirm which languages are required and test against real query samples in each during UAT.
How long does a campus automation agent take to deploy?
The Discovery Sprint is two weeks. A focused first scope — typically enrolment queries and helpdesk routing — takes six to ten weeks from Sprint sign-off to live traffic, depending on SIS access, data quality, and the number of query types in scope.
Do students interact with the agent directly?
Usually yes — via web chat, email response, or WhatsApp, depending on your existing channels. The agent's identity and escalation path are disclosed to students from the start, in line with institutional policy and the expectations of your student population.
Show us your highest-volume admin query type
In 45 minutes we will map it to your SIS, tell you whether an agent can handle it reliably, and set out what a Discovery Sprint would establish.
Book a 45-min scoping call