Innovspace — AI-native property operations

Sense7ai engineered the AI-native platform powering Innovspace's commercial property operations — a tenant-facing self-service portal across web and mobile, AI-driven workflow automation that runs the service and maintenance cycle end-to-end, and an operations data engineering layer that gives portfolio leadership a real-time view across every asset.

Built for commercial property operators running high volumes of tenant interactions, maintenance workflows, and operational decisions on processes that haven't kept pace with the portfolio's scale.

At a glance

A Sense7ai ProductLive · production

Innovspace

Commercial property operations

Engagement

Product engineering — AI-native property ops platform

Sense7ai entity

Sense7ai Inc. (Delaware)

Delivery

Engineering pod from Sense7ai Data Solutions Private Limited (Coimbatore, India)

Products

Tenant self-service portalAI workflow automationOperations data platform

Stack

TypeScript (Next.jsReact)Python (FastAPI)React NativePostgreSQLAWS

* affiliated — see disclosure below

Constraints

The challenges

Commercial property operations run at the intersection of high transaction volume, distributed teams, and fragmented tooling. Tenant interactions, maintenance workflows, and portfolio reporting all running on disconnected systems creates the coordination overhead that technology was supposed to remove.

CONSTRAINT-01Non-negotiable

REQ

Tenant experience and operations data cannot live in separate systems.

NOTE

When a tenant raises a service request, the maintenance workflow, cost allocation, vendor dispatch, and asset record all need to move together. Systems that don't share a data model don't reduce coordination — they shift it.

CONSTRAINT-02Non-negotiable

REQ

Manual workflows don't just slow operations — they cap them.

NOTE

Maintenance triage, request categorisation, approval routing, and status communication running on human effort means throughput is bounded by headcount, not demand. The AI layer had to take repeatable work end-to-end.

CONSTRAINT-03Non-negotiable

REQ

A portfolio you can't see in real time is a portfolio you can't manage.

NOTE

Occupancy, arrears, maintenance backlog, and vendor performance scattered across disconnected tools means leadership decisions run on stale data. The data engineering layer had to make the portfolio visible as it runs, not the week after.

What we built — the Innovspace platform

Tenant self-service portal

Tenant-facing web surface covering the full service lifecycle — service requests, lease communications, document access, payment workflows, and operational notifications. Built for the commercial tenant who expects a responsive digital experience. Property management team and tenant see the same underlying record from their respective role-scoped positions.

WebRole-scoped

Mobile companion

React Native applications for field and on-the-go access — facilities and operations teams logging and updating requests in the field, tenants accessing services between locations, vendor-side workflow updates against open work orders.

React Native

AI workflow automation

Intelligent routing and triage for the service and maintenance cycle — AI-assisted categorisation of incoming requests, priority prediction, vendor or team routing based on request type and availability, escalation triggers on SLA breach, and draft communications at key workflow checkpoints. Every AI-assisted routing decision stops at human approval on threshold actions (vendor dispatch above cost threshold, tenant-facing communications before send).

TriageRoutingHITL

Operations data engineering

A structured data engineering layer that consolidates tenant, lease, maintenance, and vendor data into a unified, queryable operational data model. Built so the analytics surfaces have a reliable, well-modelled foundation — not a reporting layer bolted on top of raw application data.

Unified data modelLineage

Portfolio analytics and dashboards

Real-time operational visibility across the portfolio — occupancy and void analysis, arrears and payment status, maintenance backlog by asset and category, vendor performance and SLA compliance, and operations throughput metrics. Surfaced through configurable dashboards for operations leadership and asset management teams.

OccupancyArrearsSLA

Integration layer

Connectors to the property management, accounting, communications, and document-management systems Innovspace operates — built as a first-class part of the platform so the data engineering layer has clean, reliable inputs from day one.

PMSAccountingCommsDMS

Operating tenets

Engineering approach

One data model behind tenant experience and operations analytics

The portal and the data platform share the same underlying records. A service request raised by a tenant feeds the operations dashboard without a manual sync step.

AI on workflows with a measurable baseline

AI features were applied where there was an existing manual workflow with a measurable cycle time — request triage, routing, escalation — so the platform could compare before-and-after within the engagement.

Human-in-the-loop on threshold actions

Vendor dispatch above cost threshold, tenant communications before send, and escalation actions stop for human approval at policy-defined gates. The AI handles the volume; humans own the decisions that carry cost or relationship risk.

Data engineering before analytics

The operations dashboards are only as reliable as the data model beneath them. Schema, ingestion, validation, and lineage were engineered first; the reporting surfaces were built on top.

How we worked

Dedicated engineering pod against a written SOW under the Sense7ai MSA — full-stack engineers for the tenant portal, a mobile engineer for the React Native companion, a data engineer for the operations data platform, an ML engineer for the AI workflow components, and a designer for the shared system. Two-week sprint cadence with operations-team demos; sprint review document each fortnight. Monthly steering on roadmap and risk; quarterly executive review on outcomes. Stack: TypeScript (Next.js; React portal SPA), React Native (mobile), Python (FastAPI workflow services; classifier stacks for AI triage and routing), PostgreSQL, AWS deployment.

Official · Compliance RegisterIssuedSense7ai · Compliance register

Compliance controls applied

A manifest of the compliance controls applied in this engagement, with each attestation traced to the system that implements it.

05Attestations
on file

S7AI · 06 · 05

REF · 001Verified · in production

Tenant and operational data protection

Encryption at rest (AES-256) and in transit (TLS 1.2+); role-scoped access controls

REF · 002Verified · in production

Privacy regulations

Data-subject access, deletion, and portability workflows mapped to GDPR, CCPA, and DPDPA

REF · 003Verified · in production

Decision audit trail

Structured decision traces for AI-assisted triage, routing, and escalation actions

REF · 004Verified · in production

Human-in-the-loop gates

Threshold-defined approvals on vendor dispatch, communications, and cost-bearing actions

REF · 005Verified · in production

Sense7ai adopted policy set

Information security, data privacy, incident management, cloud/DevOps

Outcomes

Program status · Innovspace · Live in productionAudited · risk-scaled · evidence-bound

The Innovspace platform is live in production across Innovspace's commercial property operations. The tenant self-service portal, AI workflow automation, operations data engineering layer, and portfolio dashboards all run inside the platform today.

Specific operational throughput metrics, tenant engagement rates, workflow automation volumes, and portfolio data coverage figures are held back until Innovspace authorises publication in writing.

Building an AI-native property operations platform? Or looking to bring AI workflow automation and real-time data visibility to an existing commercial property portfolio?

Tell us about the system you need to build — or the foundation you need to lay. Whether that means agentic AI in production, regulated software infrastructure, or a phased roadmap that grows into AI capability over time, qualified inquiries typically receive a same-day or next-business-day response; scoping calls follow within five business days, subject to availability.

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