We design and deploy custom AI automation systems for facilities management operators — taking the manual hours out of work orders, PPM compliance, procurement and client reporting, and handing them back to your team as capacity and margin.
Tenant complaint · Chiller noise, Tower B L14
Routed to HVAC crew · SLA 4h
Fire damper inspection evidence pack
Compiled · 34 assets · awaiting sign-off
Subcontractor quote vs rate card
3 variance lines flagged · $4,180
Contract SLA pack · 12 sites
Generated with commentary
Built for facilities management operators · sample references
One vertical. All the way down.
Generalist automation shops spend the first month of every project learning your industry on your budget. We already speak facilities management, so day one starts at the operational detail that actually decides whether an automation survives contact with a live site.
“Niching down is not a limitation. It is the reason our third client's system took six weeks instead of six months.”
NARASIMAN delivery principle
Portfolio scale
Multi-site, multi-service operators — hard services, soft services, mixed-use towers, hospitals, campuses and industrial estates.
Field reality
Automation designed around what a technician can realistically do with gloves on and one bar of signal.
Systems we wire into
Core systems
Each one is built for your data, your SLAs and your stack — not configured from a template. Start with the single highest-payback system, then compound.
Every inbound request classified, prioritised and routed in seconds.
Reads tickets arriving by email, WhatsApp, tenant portal or phone transcript. Extracts asset, location and fault type, scores urgency against the contracted SLA, assigns the right trade team and drafts the acknowledgement reply for a human to approve.
~320 hrs/mo of manual triage removed
Planned maintenance and HSE evidence that assembles itself.
Turns PPM schedules, statutory requirements and site-specific method statements into technician checklists, then compiles the completed evidence — signatures, readings, photos — into an audit pack the client can accept without chasing.
Audit pack prep cut from 6 days to 4 hours
Subcontractor quotes normalised against your own rate card.
Parses PDF and email quotations line by line, maps each line to your agreed rate card, flags variance and scope creep, and produces a comparison sheet with a recommended award and the reasoning behind it.
Quote review cycle down 71%
A technician's voice note becomes a structured job report.
Technicians speak or photograph what they found. The system transcribes, extracts parts used, labour time, asset condition and follow-up actions, and writes it straight back to the job record — in the language the site works in.
Report completion rate up to 98%
Monthly SLA and KPI packs, generated the moment the month closes.
Pulls job, SLA and cost data on a schedule, writes the commentary a contract manager would write, highlights breaches with root-cause candidates, and delivers a branded pack per client contract.
12 contract reports produced in one run
See the failure before the callout.
Watches asset history, callout patterns and consumption data to surface assets drifting toward failure, spare-part demand spikes, and the sites quietly eroding your contract margin.
Reactive callouts reduced 23% in pilot scope
Metrics shown are illustrative ranges from comparable scopes, not guarantees.
Where we win
Enterprises get quoted a year-long programme or handed a brittle no-code flow. We deliberately built for the space in between: real engineering, one sector, fixed price, ninety days.
Sector depth
NARASIMAN
Facilities management only — SLAs, PPM, CAFM, HSE
Time to production
NARASIMAN
90 days to a live system
What you actually get
NARASIMAN
Custom AI systems wired into your stack
Price shape
NARASIMAN
$18K per system · ~$6K/mo, flat
Who owns the outcome
NARASIMAN
We do — measured against your KPIs
After go-live
NARASIMAN
Named engineers, monitoring, next wave planned
Comparison reflects our own positioning against these categories of provider. Company names are referenced as category examples only.
The 90-day programme
We sit inside your operation, not in a workshop.
One system, chosen for payback — not for demo value.
Wired into the stack your teams already live in.
Prove the savings, then compound them.
Blueprint studio
This is the first thirty minutes of a real NARASIMAN audit, run live in your browser. Tell us how a process works today and our AI architect drafts the agent workflow, integration points, human checkpoints and expected payback.
Blueprint Studio runs on your own AI account, so every generation stays under your billing and your data policy. Add one of these project secrets and the studio goes live immediately — no code changes needed.
OPENAI_API_KEY
From platform.openai.com → API keys
GEMINI_API_KEY
From aistudio.google.com → Get API key
Your blueprint will appear here
Agent workflow, systems to integrate, human checkpoints and an estimated payback window — structured exactly like the ones we present in a paid audit.
Engagement models
Priced in USD for global buyers, engineered from our India base. Flat fees, no change-order games, and the audit fee credited back when you proceed to a build.
Find out exactly what is automatable before you commit to a build.
$2,400
one-time · 2 weeks
One production AI system, designed, built, integrated and proven.
$18,000
per system · ~$6,000/mo over 3 months
A standing automation team for operators running multiple systems.
$6,000
per month · rolling
Where we are heading
Forward-looking plan, not a performance claim
Today
4 active engagements
Four facilities management operators running NARASIMAN systems at an effective $6K per month each.
Year 2
11 operators
Deepening in the same vertical: every new system reuses hardened FM connectors and playbooks.
Year 3
22 operators
USD retainers, delivered from a low-cost India engineering base — enterprise capability without enterprise overhead.
In their words
Placeholder quotes — fictional names and companies, held here until client references are approved for publication.
The triage agent took our helpdesk backlog from four hundred open tickets to under thirty in six weeks. Nobody on my team wants to go back.
We had been quoted eleven months by a global consultancy. NARASIMAN had something live in our CAFM in under ninety days, for a fraction of the fee.
They understood SLA penalty logic on the first call. That never happens with automation vendors — usually we spend a month teaching them our world.
Questions
Still unsure whether your operation is ready to automate? Ask us directly — we will tell you honestly, including when the answer is “not yet”.
Ask a questionGet started
Tell us where your operation hurts. We will come back within one business day with the two or three processes we would automate first — and what we think they are costing you today.
