4-11% Transformation success rate in legacy-heavy sectors
Against 26% in digitally mature industries. Fewer than 30% of transformations improve performance and sustain the gain.
Public sector
Technology averaging twenty years old, and a transformation success rate between four and eleven percent.
The programmes fail for the same reason every time: they try to replace the system instead of relieving the pressure on it.
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65%
of government agencies run critical systems on COBOL, with technology averaging 20 years old.
Source: GAO-25-107795: Agencies Need to Plan for Modernizing Critical Legacy Systems
What is happening
The mainframe is not the problem. Nobody can get a straight answer out of it.
2.5 Digitalisation score, the lowest of any sector
Not from lack of intent. From procurement cycles, fragmented regulation and systems nobody can safely touch.
Backlogs return after every clearance effort
Because the effort addresses the visible queue rather than the process that generates it.
Procurement selects for the wrong thing
Fragmented, hard to navigate rules favour vendors who are good at bidding over vendors who are good at delivering.
Intelligence, plumbed in
A scanned form can become a case record without anybody retyping it.
Underneath: a one-way read of the mainframe, a copybook mapped to plain fields, and an accuracy figure you can publish.
How we make AI survive real data-
Connectors -
A semantic layer -
Evals you can check
What changes
Judge us on this, not on what we built.
No rip-out Relief without replacing the system of record
The legacy system keeps doing what it does. We build the access, reporting and workflow layer around it, and that takes months, not years.
Backlog Queues that reduce and stay reduced
Because the work targets the generating process, with the measurement in place to prove it held.
Auditable Every decision traceable by design
Which is a requirement here, not a feature — and far easier to build in than to retrofit.
Research
We wrote a full page on each of these, with the sources.
Each one carries its own figures and the citations behind them. Start with whichever sounds most like your week.
However hard, whatever it is
The mainframe is one example. Bring the whole backlog if you like.
We wrote this about reading a legacy system of record. If yours is a service nobody can complete online, or a queue nobody can see, same method.
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01 We sit with you
Days where the work happens, not a workshop in a meeting room. We watch the job get done and write down the shortcuts nobody wrote down.
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02 We read everything
Your data, your rules, your vendors and their documentation, and the published research on your sector. We report what is actually in there.
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03 We break it to first principles
Not which tool fixes this. What is actually causing it, taken apart until we reach the piece that cannot be divided further.
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04 Then we build
Weeks, not quarters. By this point we are not guessing what to build, and guessing is the thing that makes projects long.
Where we sit
The mainframe stays. We build what the public and the desk can use.
4
What you get
- No rip-out Relief without replacing the system of record
- Backlog Queues that reduce and stay reduced
- Auditable Every decision traceable by design
3
Built new for you — none of this exists in your stack today
- A form a citizen can finish on a phone in one sitting
- A case queue that shows the oldest first, not the newest
- A kiosk for offices where people still walk in
2
The service layer Reads the system of record. Writes nothing into it without your rules.
Connectors, one agreed meaning per field, and a model reading what no
field holds. Accuracy measured on your own records.
1
- COBOL / mainframe
- SAP
- Oracle
- legacy case management
- GIS
What you already run — unchanged, and still yours
If the mainframe knows it, we can get it out. COBOL copybooks, a green screen, a printed report, a scanned form. All of it can be reached.
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No API -
No documentation -
A terminal from 1994 -
It arrives as paper -
The vendor said no -
It reports nothing
Not a list of limits. Name yours on the call.
And once we can reach it, a model can read it. Most of the value here is in the sources nobody ever structured — the note, the letter, the screen.
Who this is for
The people who feel this first
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Director of Digital -
Chief Information Officer -
Programme Director -
Head of Service Delivery -
Procurement Lead
Straight answers
The questions you would ask on the call
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Can you work with a mainframe we cannot modify?
Yes, and that is usually the right constraint. We read from it — through extracts, APIs or a replica — and build alongside. Not touching the core is what makes the timeline realistic and the risk acceptable.
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How do you handle procurement requirements?
We scope to fit inside your thresholds where that makes sense. We start small, so value is proven before you commit further. And we produce the paperwork your process needs without treating it as a nuisance.
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Why do these programmes usually fail?
Most attempt replacement. The replacement is specified against today's understanding, takes three years, and meets a changed world. Relieving pressure on the existing system delivers value in months and does not require anyone to bet a service on a migration.
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Can AI read what the mainframe prints?
Yes. A screen or a printed report is enough. We publish the accuracy figure, so the desk knows exactly how far to trust it.
Also in public sector
Next step
Start with your own numbers.
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We talk
20 minutes. Free.
You tell us what is not working. We ask how the work really gets done.
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We look at your data
A few weeks.
We read your systems, including the notes and letters no field holds. You get what is really in there, what it costs, and the accuracy we can hit.
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We build
A few months.
Only if step 2 says it is worth it. Fixed price, agreed before we start.