- Developer toolingIndustry
- Engineering teamsClient
- AI AgentsCategory
- Fast to valueTime to impact
The challenge
- General code assistants are strong on mainstream languages but weak on legacy stacks like 4GL and Informix, and they burn tokens scanning everything.
- Teams maintaining old systems need depth there, cheaply.
A code analyzer tuned for efficiency and legacy languages like 4GL and Informix, at a fraction of the tokens.
A focused code analyzer and reviewer that earns its place next to general tools by specialising where they struggle: efficiency and old languages like 4GL and Informix. It works only on the context you give it, which cuts token consumption dramatically.
What we built
- 01Specialises in legacy languages like 4GL and Informix.
- 02Focuses the review on efficiency, not just correctness.
- 03Works only on the context you provide.
- 04Cuts token consumption dramatically as a result.
How it works
What it can do
Legacy languages
Built for 4GL, Informix and other old stacks.
Efficiency focus
Reviews for performance, not just bugs.
Context-scoped
Works only on the context you give it.
Low token cost
Dramatically less token consumption.
Who stays in the loop
The call the system deliberately does not take, and what the person is given to take it with.
A focused code analyzer and reviewer that earns its place next to general tools by specialising where they struggle
The engineer who owns the code
Decideswhich findings are worth fixing
Seeseach finding with the exact code and context it was drawn from
The payoff
What is different once it is running. No invented numbers: these are the changes the work was built to make.
Reviews 4GL and Informix that general tools stumble on, focused on efficiency, at a fraction of the token cost.
Depth on legacy stacks that general tools miss.
Reviews focused on efficiency.
A fraction of the token cost.
Built with
The layers this runs on, from what comes in to what it plugs into.
- Model layer
- LLM
- Context-scoped analysis
- Runs on
- 4GL / Informix
Common questions
The same answers as above, written out.
A focused code analyzer and reviewer that earns its place next to general tools by specialising where they struggle: efficiency and old languages like 4GL and Informix. It works only on the context you give it, which cuts token consumption dramatically.
General code assistants are strong on mainstream languages but weak on legacy stacks like 4GL and Informix, and they burn tokens scanning everything. Teams maintaining old systems need depth there, cheaply.
Point it at the code and context that matter. It analyses for efficiency and legacy-language issues. You get focused findings at low token cost.
The engineer who owns the code decides which findings are worth fixing. They see each finding with the exact code and context it was drawn from.
Model layer: LLM, Context-scoped analysis. Runs on: 4GL / Informix.
Depth on legacy stacks that general tools miss. Reviews focused on efficiency. A fraction of the token cost.
Where this fits
The practice it belongs to, how an engagement like it runs, and what we have written about the subject.
- Developer tooling
- Legacy
- Code review
- Efficiency
- Developer tooling
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We are a small team of senior specialists. We pick the right model and the right layer, and we build the least machinery that does the job. You get a call with an engineer, not a sales deck.