Maximum AI Platform
Meet Max.
The AI capability layer behind AkimTech — a private inference engine that reads, understands, and answers from your documents, built on dedicated GPU hardware with a managed cloud backbone standing by.
The AI capability layer behind AkimTech — a private inference engine that reads, understands, and answers from your documents, built on dedicated GPU hardware with a managed cloud backbone standing by.
When an AkimTech application needs to read a document, understand it, or answer from it, that work runs through Max. It isn't a single program — it's the whole AI capability stack: the hardware, the secure bridge that serves the models, the models themselves, and the applications they power.
A dedicated GPU runs the models, Ollama serves them, nginx guards the door, and the cloud catches the overflow.
The bulldog is the face; this is the engine room.
A dedicated NVIDIA Tesla T4 GPU server — real hardware for heavy lifting, not a shared slice.
An nginx edge with TLS and token-gated access — the models are never exposed to the open internet.
A deliberate roster of open models — general reasoning, chat, and document OCR — each chosen for a job.
The products people actually use — ISONAR, Admissions, and the broader AkimTech family.
Max speaks through open models, each chosen for a job. On document OCR, an active bake-off is scored on real legal and treasury documents — the lead model decided on evidence, not assumption.
Contact Sales →Max is the engine; the applications are what people use. New applications plug into the same platform — and graduate to their own dedicated GPU as their volume justifies it.
Legal & government document intelligence — reading and structuring court filings, treasury records, and government documents. The OCR-first workload Max was built around.
K-12 college-pathway planning — the education-facing application of the family, fitting for the graduate in the cap and gown.
The platform is built so additional applications can plug into the same secure endpoint, each able to scale onto its own dedicated hardware when the time comes.
The model server never faces the internet directly — a hardened edge is the only entrance.
Every request is authenticated before it ever reaches a model. No token, no answer.
Documents are read on the box, and output is sanitized of personal information before anything reaches the cloud.
Sensitive workloads — such as K-12 data — run on their own hardware rather than sharing a box.
Talk to our team about bringing private, GPU-backed AI to your mission.
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