Every Engineer On Shift
Is Your Best
AssetBlue is a domain-specialised SLM that captures how your best engineers reason — and makes that judgment available to every engineer, every shift. No sensors. No integrations. No waiting for a callback.
Experts are retiring. Failures are accelerating. Costs are mounting.
Your best diagnosticians can only be in one place at a time — and they're leaving faster than the industry can replace them. Every unplanned shutdown is a reminder.
If the same problem happened at another thermal plant, we don't have access to that knowledge. We call NTPC, call BHEL, wait for callbacks.
A comprehensive list of failures of that particular equipment worldwide — that would be helpful.
We have a history book only. If he has not faced such problems, he can go through that — he'll get some idea.
Industrial reasoning breaks traditional AI.
Complexity explodes
Industrial systems are highly interconnected. As variable count rises, the space of possible causal structures grows too quickly for naive discovery.
Failure data is sparse
Critical assets don't fail often enough to generate rich training data. Real-world failure events are rare, uneven, and incomplete.
Black boxes don't earn trust
Classification models can label likely causes, but they can't show the reasoning path, causal mechanism, or evidence chain behind the answer.
Expertise doesn't scale
Traditional RCA methods like 5 Whys and FTA are powerful, but they remain manual, slow, and dependent on scarce experts.
¹ Siemens, The True Cost of Downtime, 2024. ² APQC “Great Retirement” survey. ³ Pew Research Center, “Baby Boomers Retire”, 2023. ⁴ AssetBlue field research, 2025. ⁵ ABB Value of Reliability survey. ⁶ AssetBlue field research, 2025.
Not just when things break. When things don't look right.
The same reasoning engine that supports post-failure diagnosis helps engineers investigate anomalies before they become shutdowns.
An engineer opens AssetBlue, describes what they're seeing or hearing, and shares a photo or video. The system reasons through possible causes, retrieves similar patterns from prior cases, and helps the engineer investigate before the issue escalates.
Structured reasoning. Not keyword search.
AssetBlue guides engineers through structured investigation using Fishbone, 5 Whys, Fault Tree, and FMEA — not as static templates, but as live reasoning paths.
Senior gets speed. Junior learns reasoning.
Most systems return an answer. Coach Mode walks junior engineers through the why — what to observe, what to rule out, why each question matters. Veterans move fast. Juniors build judgment. Same session. No mode to select.
Four worries. Four answers.
Cases persist across shifts
A Case survives shift changes, dead batteries, and interruptions. Any engineer can continue from where it stopped.
Case-basedEvery output has a next step
Every hypothesis includes the action, the owner, the priority, and whether it’s safe without supervisor sign-off.
Action-completeEvery claim cites its source
Traceable to a case study, OEM standard, or technical reference. Tappable. Disputable.
Cited and verifiableOne asset model, many industries
Boilers recur across power, oil & gas, chemicals, steel, cement, pharma, and more. Model the asset deeply — every industry inherits it.
Horizontal reuseOne corpus. Every industry where boilers are critical.
V1 is validated for industrial boilers — the highest-failure-frequency asset in every sector below. If your plant runs boilers, AssetBlue is ready today. Additional asset classes are in active development.
Questions from every plant visit.
Describe the problem.
Let's reason through it together.
Request a demo. We'll walk you through a live diagnostic session in 30 minutes. Or request a pilot implementation with your asset class.
From the team that built Embibe — India's largest AI education platform, backed by Reliance Jio.