For fleet and asset-heavy operators running TM Master or another planned-maintenance system. Most have years of maintenance history sitting in old or migrated systems, written down and never read. We clean it up, recover the failures buried in the notes, and use proven reliability math to show what takes your vessels off hire. Fixed price. Gated. If the answer is no, you get that in writing before you fund a build.
Downtime is concentrated in a few major breakdowns, and every day off hire forfeits the full day rate. The warning signs are usually already in your records, carried across one system change after another. They sit in three places no report reads.
A failure written in an engineer's note never reaches the failure count, so equipment can look on schedule while it keeps breaking down.
The system shows what was postponed, not what happened next. Nobody can see which deferred jobs turned into breakdowns.
Off-hire days live in the commercial system. Their causes live in the maintenance system. No report puts them side by side.
Sensors and predictive tools are arriving, and they need a clean failure history to learn from. Few fleets have one. Most teams look at their older records, see how messy they are, and decide they are unusable. Usually they hold more than anyone expects.
What are off-hire days costing your fleet?Enter your vessel classes, day rates, and off-hire days. See what the warning signs already in your records could be worth.Most reliability programs start with new sensors and a new platform. We start with the history you already own. Send us one export from your maintenance system and the off-hire report you already keep. We clean it up, find what it can already answer, and show where the money is. Everything after that is staged, so you only fund what the evidence supports, and you own everything we produce.
Whatever system they came from, including records carried over from earlier ones. Every record is cleaned, preserved, and graded for trust, then built into one master record per vessel that your team can search and ask questions of.
We recover failures written only in the notes, link each deferred job to what happened next, and rank equipment by off-hire impact: the days it costs, not the label it carries. Every finding is confirmed before it counts.
Phase one covers one vessel class at a fixed price. Proven reliability math sizes both returns from your own records: off-hire days avoided, and scheduled work that could safely be done less often. It ends in a written go or no-go with a confidence figure.
Only what cleared the gate gets built, priced firm from the evidence. Later phases add fleet-wide forecasting, cost data, and condition signals, and sensor or predictive partners build on the same clean history. You can stop at any gate.
An offshore fleet operator had years of maintenance history spread across TM Master and the systems before it. Like most fleets, they had decided much of it was unusable. They handed us one raw export. No new data was collected and nothing was installed. Everything below came out of records they already owned.
of job history, including records carried over from earlier systems, cleaned into one database the team can question
of failure, leak, replacement, and overhaul events recovered from free-text notes no report had ever counted
risk ranking, with life-used estimates for the components that matter most
for each data-quality gap surfaced, traced back to the record it came from
One component had a few scattered entries across several vessels. In the maintenance system they were just rows. Read together, they showed equipment running several times past the life its own history supports, and one unit likely to fail within months. That is the difference between a maintenance log and an answer.
That working session became a fixed-price first phase, now underway: cleaning up the full history so the math can show what takes vessels off hire. It ends in a written go or no-go with a confidence figure.
If your history lives in it, we can work with it. Records carried over from earlier systems, retired codebooks, and half-empty fields are the normal case, not a blocker. The real story is usually in the free text nobody has read at scale.
TM Master and other planned-maintenance systems, CMMS, and EAM platforms holding years of job history, deferrals, components, and spares.
Off-hire reports, day rates, cost, and procurement data. It ties each breakdown to what it cost, in a dollar figure a board can act on.
Records carried over from earlier systems, pre-migration archives, and retired codebooks. We clean, decode, and preserve them so nothing is lost in the next move.
Engineer notes, work-order comments, and logs. Failures written only in the notes never reach a failure count. We read all of it and confirm what we find.
Oil analysis, vibration, temperature, and OEM monitoring feeds. Predictive tools need a clean failure history to learn from. We build that first, and they layer on top.
If you already run a lake or warehouse, we build on it. If you do not, we stand up a working set your team can query from day one.
Phased and gated. Phase one covers one vessel class at a fixed price, starting from one export of your maintenance system and the off-hire report you already keep. It cleans and structures the history, recovers and ranks failures by off-hire impact, and ends in a written go or no-go with a confidence figure. Later phases add fleet-wide forecasting, cost data, and condition signals, priced firm from the evidence. You can stop at any gate.
No. Phase one runs on a flat export from the system you already run, whether that is TM Master or another planned-maintenance system, plus your existing off-hire report. Nothing installed, no new sensors, and no change to how your crews and engineers work.
Then you get that answer in writing, with the reasoning and a confidence figure, for a fixed price. A no-go still leaves you a clean, searchable history, a costed answer, and a ranked data-quality register. That is a far cheaper way to find out than after a build.
Messy is the normal case, especially for records carried over from earlier systems. Older entries often record that a job was due, not what was found. So every record is graded for trust, every recovered failure is confirmed before it counts, and no forecast is relied on until it passes a backtest against events already on record. Sometimes the answer is a smaller build than hoped. You will know before you spend.
AI reads the free-text notes, so failures written only in comments can finally be found and counted. The analysis itself is established reliability math, and every forecast shows its reasoning. Nothing rests on a black box.
We plan for your process instead of pretending it away. Read-only access, least privilege, and your infrastructure where required. You own everything we produce. Client data is never used to train models for anyone else and never shows up in anyone else's engagement. Delivery clocks start when access is confirmed, so review time never eats delivery time.
No. TM Master and your other systems stay exactly where they are. We build a clean, vendor-neutral layer beside them that your team, and any sensor or predictive partner, can build on. If you migrate systems later, that clean history carries with you instead of being lost in the move.
Tell us where the work runs through you. We'll find the bottleneck, quantify the ROI, and tell you honestly whether automation will pay off.