Every engagement is different. Some are best served by a low-code enterprise platform a client already owns, some by a product, and some by a custom application. Diamax works in all three, alone or in combination, according to what the objective requires.
Diamax is proficient in a wide array of base technologies and languages. Most of our current work involves Microsoft .net, Microsoft SQL Server, Azure, AWS, AWS SES as well as an assortment of front-end frameworks. Given how long our team has been active and how many integrations we have completed, the list of technologies we know is longer than most information systems consultancies.
AI is integral to our research, design, coding, testing, deployment, and maintenance. The architecture is ours, and AI is applied in a manner that preserves the firm's standards for security, performance, scalability, adaptability, and maintainability. Each member of the team remains accountable for what they produce, which includes being able to read, diagnose, and revise it without assistance.
Acceleration is now something a client can choose to buy. An engineer working at full pace against a substantial model budget can consume a considerable amount of capacity in a month. That dimension did not exist three years ago, and how far a client turns it up depends on the problem: some engagements require little, while an executive office facing something sufficiently consequential will accelerate the work well beyond what would appear reasonable elsewhere.
What changes is not only the schedule. It is when the important conversations become possible. We can prototype in the second week, put several interface directions in front of the people who will use them, and map a complex journey end to end long before an engagement would ordinarily reach that point. For a firm whose method is to find where a documented process stops being sufficient, that matters: we can build the exception path and watch someone use it, rather than describing it in a workshop and discovering the difficulty in month five.
The constraint is not access to the models. It is whether a team can work at that rate and still deliver something a client would want in production. Volume without architecture, senior review, and evaluation produces a great deal of code and very little that can be depended upon. Acceleration is therefore offered in defined intervals rather than as a standing rate.
Not everything requires a frontier model. We use the strongest models available for design, exploration, and difficult problems, and smaller or local models for maintenance and routine operation, including servers in our own offices for work that should not leave them. A system intended to run for twenty years needs a compute strategy that does not assume today's economics will hold.