QUAICU/Solutions
04 SOLUTIONS

Sector-specific
operating software
on one unified kernel.

Not feature bundles. Complete operating environments where every AI action is governed by the same kernel, under sector-specific rules.

SIX SECTORS · ONE KERNEL
04·1 SECTOR MATRIX

Six sectors. Same AI Governance. Different regulatory pressure.

Sector Product Status Key Drivers
Universities (India) ALIS LIVE NAAC · NBA · UGC · NIRF · DPDP · faculty workload reduction
Healthcare RICO DESIGN PARTNERS ABDM · clinical decision support · traceable AI · PII protection
Hospitality FERO DESIGN PARTNERS DPDP · multi-property orchestration · governed personalisation
Real Estate POLO DESIGN PARTNERS RERA · document governance · sales lifecycle automation
Law Firms LEMO FUTURE Attorney-client privilege · confidential processing under the firm's IT policy
Banking & Finance CIRO FUTURE RBI mandates · transaction integrity · compliance traceability
COMMON FOUNDATION

Across all six.

Every AI action passes through your approval. Your data stays separate from every other customer's. End-to-end recording. One product underneath, six regulatory contours on top.

NAAC · NBA · UGC · ABDM · RBI · DPDP
04·2 AGENTIC OPERATIONAL LAYER

A workforce of AI helpers,
behind everything your team runs.

A fleet of AI helpers handles the repeatable work behind running your institution. Every action they take is checked against your rules and your approvers, so nothing happens that shouldn't.

WHAT THEY DO · 01

Run the paperwork

Multi-step workflows that used to need a queue of handlers, intake forms, eligibility checks, document assembly, status follow-ups, now run by themselves. Your rules keep every step on the rails.

WHAT THEY DO · 02

Coordinate across departments

Work that crosses admissions, finance, academics, and communications no longer needs someone stitching it together by hand. Humans step in only at the points your policy says they must.

WHAT THEY DO · 03

Catch issues early

A reconciliation gap, a missing approval, a number that does not match, the helpers surface it to the right person before it grows into a problem. They suggest. People decide.

RUNNING AGENTS · ALIS
ADMISSIONS_INTAKE ELIGIBILITY_CHECK DOC_ASSEMBLY FEE_RECONCILIATION GRIEVANCE_TRIAGE RESULT_AUDIT ACCREDITATION_PACK RESEARCH_GRANT_SCOUT STAKEHOLDER_NOTIFY

Every move each helper makes is logged with the rule it followed, in case anyone ever needs to ask why.

WHAT THE CLIENT FEELS
  • → Cross-department admin queues compress into a single workflow with governed AI on every step.
  • → Exceptions caught at intake, not at audit.
  • → Cross-department handoffs collapse from days to minutes.
  • → Leadership sees signals before they become incidents.
WHAT YOUR RULES GUARANTEE
  • → No helper can change a record outside the steps you have approved.
  • → No AI suggestion slips past a policy review or a human approver.
  • → No action goes unrecorded, and the log cannot be edited after the fact.
  • → Each customer's data stays separate from everyone else's.
AGENTS PROPOSE · KERNEL DECIDES
04·3 EDUCATION IN DEPTH

Beachhead vertical.
Live. Productised. Repeatable.

PRESSURE · 01

Student data protection

DPDP Act, institutional policies, parental consent regimes.

PRESSURE · 02

Research confidentiality

Unpublished findings and grant material are institutional IP.

PRESSURE · 03

Accreditation & governance

NAAC, NBA, NIRF demand transparent process and complete audit trails.

WHY GENERIC AI FAILS
  • × Cloud platforms put institutional workflows under someone else's governance regime.
  • × Pricing scales with adoption, so unit economics decay as the institution actually uses AI.
  • × Accreditation cycles become reactive evidence scrambles.
WHY ALIS WORKS
  • → Deployable under the institution's IT policy, with per-tenant isolation.
  • → Institution-wide. Admissions, academics, exams, finance, HR, research, library, placements one governance plane.
  • → Complete auditability. Every AI interaction logged with user context, timestamp, inputs and outputs.
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