Prognexis is a standards-compliant Prognostics & Health Management platform that unifies condition monitoring, RUL prognostics, energy intelligence, and operational control across your entire critical asset fleet — electrical, mechanical, and utility systems.
The Prognexis UCC platform is domain-agnostic at its core. Shared services handle prognostics, anomaly detection, and decision support — asset-specific modules plug in on top.
Live at ucc.prognexis.co.in
Prognexis builds a digital twin and PHM model for every asset class. Support is added iteratively — availability shown below.
Prognexis combines ISO 13374 PHM rigour with utility cost intelligence, energy optimisation, and ESG tracking — in a single converged platform.
Live digital twins for every asset — parameterised with nameplate data, operating history, and real-time sensor state.
ISO 13374 · L2Probabilistic Remaining Useful Life prediction with confidence intervals, fleet priors, and operating-condition correction.
ISO 13381-1Multivariate anomaly detection identifying deviation from the healthy operating envelope — catches failures weeks before threshold alerts.
Statistical PHMReal-time ₹/hr and ₹/kg cost of operation per asset, mapped to tariff slabs, fuel cost, and maintenance spend.
UCC ModuleCompressor sequencing, chiller loading, and utility dispatch optimisation — reduce energy cost without compromising availability.
UCC ModuleScope 1 & 2 emission tracking per asset with hierarchical rollup from equipment to site to enterprise for board-ready ESG reporting.
UCC ModulePrognexis is designed ground-up to satisfy data processing, prognostic, and reporting requirements of international PHM standards.
Indicative pilot scenarios — the cost of one hour of outage, the assets at the centre, and the Prognexis modules that close the loop.
VCB trip-coil aging, transformer DGA trends, and busbar thermal hotspots tracked across 80+ substations. Regulator-ready CIGRÉ TB 761 health reports replace paper inspection logs.
Screw compressor sequencing reduces ₹/SCFM, while bearing & valve PHM gives 60-day advance warning on the air system that runs the entire stamping line.
RO membrane normalised permeate flow, salt rejection drift, and WFI distribution health — predicting failures before a batch is at risk, with 21 CFR-style audit trails.
Centrifugal chiller COP tracking, UPS battery health, and MV switchgear duty all on one view. Health-aware load shifting protects SLAs while UCC tracks PUE and Scope 2.
Power transformer DGA + ageing, MV motor stator insulation, and VFD thermal derating tracked together. Compliance-grade logs for BEE PAT, IBR boiler, and ESG reporting.
Compressor train, HRSG, and TFH health tied to your turnaround plan. RUL forecasts move work into planned shutdowns instead of triggering unplanned trips.
Most platforms start with data and hope patterns emerge. Prognexis starts with deep engineering knowledge of how each asset class degrades — then uses data to confirm, calibrate, and act.
The dominant approaches to industrial predictive maintenance — generic AI platforms, pure data analytics tools, and standalone statistical monitors — share a common limitation: they are asset-agnostic by design. They treat a switchgear panel the same as a pump, a boiler the same as a chiller. That makes them fast to deploy on paper. In practice, it means months of data collection before meaningful output, and alerts that plant engineers cannot trace to a physical cause.
Prognexis is built on the opposite principle. We encode what is already known about each asset class — from ISO 13374, ISO 13381-1, CIGRÉ TB 761, and decades of field engineering — into the platform's health models before a single data point arrives. Data refines and calibrates that knowledge. The result: actionable PHM from day one, even on a new installation with no failure history.
And where other platforms stop at the alert, Prognexis closes the operational loop: health insight → cost intelligence → optimisation action → ESG tracking. One platform, not four disconnected tools.
| Capability | Generic AI Platform ML / deep learning, asset-agnostic |
Data Analytics Tool Dashboards, KPIs, threshold alerts |
Statistical / Vibration Tool Condition monitoring, rule-based |
OEM-Bundled Platform Vendor-specific digital services |
Prognexis UCC Physics-first · Standards-embedded |
|---|---|---|---|---|---|
| Works without failure history | ✗ Needs 1–3 yrs labelled data | ✗ Threshold rules only | Partial Requires baseline period | Partial Pre-built but OEM-scoped | ✓ Physics priors + fleet Weibull, day one |
| Explainable, auditable scores | ✗ Probability scores, no reasoning | ✗ KPIs, no degradation model | Partial Rule traceability, not prognosis | Partial Varies by product | ✓ ISO 13374 compliant — every score traceable |
| Multi-domain asset coverage | Partial Rotating machinery focus | ✗ Data only, no asset models | ✗ Vibration / single asset type | ✗ Own hardware only | ✓ 37+ asset types across 4 domains |
| MV Switchgear PHM (CIGRÉ TB 761) | ✗ Generic anomaly only | ✗ Not available | ✗ Not available | Partial Own-brand switchgear only | ✓ Full PD, thermal, mechanical, duty tracking |
| Energy cost intelligence (₹/hr, SEC) | ✗ Maintenance focus, no cost layer | Partial Energy KPIs, no asset health link | ✗ Not available | Partial Energy monitoring separate | ✓ Tariff-aware, per-asset, real-time |
| Compressor / chiller optimisation | ✗ Not available | ✗ Not available | ✗ Not available | Partial Energy mgmt, not sequencing | ✓ Multi-unit sequencing, min ₹/unit cost |
| ESG / Scope 1 & 2 per asset | ✗ Not available | Partial Site-level only | ✗ Not available | Partial Site-level, not per-asset | ✓ Asset → section → plant → enterprise |
| Works with sparse / manual data | ✗ Requires continuous streams | Partial Manual import possible | ✗ Sensor-dependent | ✗ Requires own hardware sensors | ✓ DQI engine handles gaps & log books |
| India-context (₹, IBR, PESO, BEE) | ✗ Global platform | ✗ Global platform | ✗ Global platform | ✗ Global platform, generic India config | ✓ Built ground-up for Indian operations |
| Time to first PHM output | 6–18 months | Days (but alerts only) | 2–4 weeks (baseline) | 3–12 months (hardware + integration) | ✓ 4–8 weeks to full PHM outputs |
Assessment based on publicly available product documentation and industry research. Last reviewed May 2026. Individual platform capabilities may vary.
Whether you want a managed dashboard or want to embed PHM intelligence into your own systems — Prognexis has a path for you.
Full platform access, dedicated onboarding, and direct access to our engineering team. No commitment required.
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Each Prognexis product is a domain-specific PHM application running on the shared UCC platform — bringing deep asset-class expertise without rebuilding the intelligence engine.
Monitor asset health, track energy costs in real time, and optimise utility operations — all in one unified dashboard. We'll onboard you within 24 hours of your request.
MV Switchgear Prognostics & Health Management
Rotating Machinery & Compressed Utility PHM
Water, Effluent & Treatment Plant PHM
Thermal Asset Health — TFH, Boiler & Heat Recovery
Power Transformer, Motor & Drive PHM
All Prognexis products run on the same UCC core — digital twin registry, Weibull RUL engine, Mahalanobis anomaly detection, alarm manager, and decision engine. Asset-specific modules extend the platform without rebuilding it.
Unified Condition & Control — Energy, Cost & ESG Intelligence
Prognexis was founded to close the gap between how critical industrial assets are monitored today — and how they should be.
Across utilities, manufacturing plants, and power infrastructure, the dominant maintenance model is still reactive — fix it when it breaks. The alternative, time-based preventive maintenance, schedules work whether it's needed or not. Both are expensive. Both leave money and uptime on the table.
Condition-based maintenance — acting on what the asset is actually telling you — has been standard in aviation and heavy industry for decades. But the tools required have remained out of reach: digital twins, prognostic engines, standards-compliant health scoring, real-time cost intelligence.
Existing approaches each solve part of the problem. Generic AI platforms need years of failure data. Data analytics tools fire alerts after breaches, not before failures. Statistical monitors cover single asset types. OEM-bundled platforms work best on their own hardware. None of them close the loop from health insight to cost intelligence to operational optimisation — and none are built for Indian industrial context.
Prognexis changes that. We've built the full PHM stack — from data acquisition through to RUL prediction and operational control — on a single converged platform. Standards-compliant. OEM-agnostic. Deployable in weeks, not years.
To make condition-based intelligence the default for every critical industrial asset — not a privilege of the largest operators, but a practical reality for any plant that cannot afford unplanned downtime.
Every algorithm, every health score, every RUL number is grounded in a published standard or peer-reviewed model. We don't ship black boxes.
An operator should always understand why the system raised an alarm. Confidence intervals, contributing factors, and audit trails — always.
One codebase. One data model. One set of shared services. New asset types plug in — they don't require a new product.
Our first 10 pilot customers shape the product roadmap. We embed ourselves in their operations until the platform is delivering measurable value.
ESG and CO₂ tracking isn't a bolt-on. It's built into the asset model from day one — because energy efficiency and asset health are the same problem.
Tariff structures in ₹/kWh. Cost intelligence in ₹/hr. Compliance with IBR, PESO, BEE. Global standards, local context.
Engineers, data scientists, and domain experts who've spent years inside industrial operations. Team details coming soon.
Join our pilot programme and shape the platform.
We're working with our first 10 pilot customers to prove the value and refine the product. If you run critical industrial assets, we want to talk.
Whitepapers, standards mapping, FAQ, and the engineering background behind every Prognexis health score.
Every Prognexis health score traces to a clause. Below is the mapping of standard → platform module → output.
How fleet-Weibull priors combined with operating-duty correction produce calibrated RUL estimates on day one of deployment, with worked examples on a 33kV VCB population.
Why threshold alarms fail in multivariate spaces, how Prognexis builds the healthy envelope per asset class, and how detection precedes threshold breach by 2–8 weeks.
For maintenance heads & CFOs — how the UCC Cost Intelligence Engine maps every health alert to an ₹/hr exposure and a tariff-aware optimisation action.
A clause-by-clause walk-through of how Prognexis implements ISO 13374 §5.2–5.6, with auditable traces from raw sample to decision support output.
Worked pattern showing how UCC sequencing combined with MECH health scoring achieved an indicative 11% drop in ₹/SCFM while extending MTBF.
How asset-level energy data rolls up to plant-level EnPIs, SEC benchmarks, and a board-ready ISO 50001 report — without spreadsheet stitching.
JWT-authenticated REST endpoints exposing every asset's health index, RUL with confidence intervals, PoF (30/60/90/365d), and decision recommendation. ISO 13374-compliant JSON.
Prognexis ingests data over MQTT for streaming telemetry, a Manual Data Connector for log-book entries, CSV upload for batch and historical loads, and an industrial-protocol IoT Gateway — secure, tested, and field-proven.
Most pilots are producing first health scores within 2 weeks and full RUL outputs within 4–8 weeks. Because Prognexis ships with physics priors and fleet-Weibull models per asset class, we do not need 6–18 months of failure history before scores become meaningful.
In most cases, no. Prognexis is designed to extract maximum value from existing relay, SCADA, EMS, and CMMS data, supplemented by manual log book entries through the DQI engine. We will identify specific sensor gaps during scoping; new sensors are recommended only where the marginal value is clear.
Yes. The Data Acquisition Layer supports OPC-UA, Modbus TCP/RTU, IEC 61850, DNP3, BACnet, and direct REST/MQTT ingestion. We have working integrations with most major SCADA and EMS platforms; bespoke connectors are typically a 2–3 week effort.
All traffic is TLS 1.2+ end-to-end. Sensitive data is AES-256 encrypted at rest. The platform is OWASP Top-10 hardened with JWT auth, rate limiting, and CSP headers. For sensitive sites, we offer air-gapped on-premise deployment. Your asset telemetry is never shared with third parties or used to train cross-customer models without explicit written consent.
No. Every Prognexis health score is traceable to an ISO 13374, ISO 13381-1, or CIGRÉ TB 761 clause. The platform shows the contributing factors, the reference standard, and the confidence interval for every prediction. Auditors and regulators can interrogate the logic behind every number.
Pilot duration is typically 12 weeks. Scope: one product (e.g. SWGR) on one asset class, on a representative population (8–20 assets). Prognexis engineers handle scoping, integration, and onboarding. Output: a measurable PHM baseline, validated RUL predictions, and a path to wider rollout. No commitment beyond the pilot.
Pilot commercials are scoped per engagement and typically cover engineering effort plus platform access for the pilot duration. Production licensing is per-asset/per-year with volume tiers; OEM and enterprise white-label terms are available. We will share an indicative commercial after the technical scoping call.
Prognexis Technologies ("Prognexis", "we", "us", or "our") operates the website at prognexis.co.in and the UCC Platform at ucc.prognexis.co.in. This Privacy Policy explains what personal data we collect, why we collect it, how we use it, and your rights under applicable law including the Digital Personal Data Protection Act, 2023 (India).
For any privacy-related enquiries, contact: [email protected]
We collect only what is necessary for the purposes described below:
We do not sell, rent, or trade personal data. We may share data with:
Asset telemetry data is never shared with third parties outside your organisation without your explicit written authorisation.
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Prognexis Technologies · [email protected] · prognexis.co.in