Research & Development
The Engineering Behind the Intelligence
AI changes weekly. The companies that keep up are not buying tools — they are running R&D continuously. That is what we do.
Your AI stack will be outdated before your next contract renews.
The methods that defined AI in 2024 are already being replaced. New architectures, new retrieval techniques, new memory systems — they ship weekly. Argus runs a continuous R&D pipeline that tests every new approach against real workloads. What we build reflects what actually works today.
Where We Work
Open Source Model Training
A fine-tuned open-source model consistently outperforms a generic model ten times its size on domain-specific tasks. We train and optimize on our own infrastructure — legal corpora, financial filings, clinical records. No API dependency. The model belongs to the deployment.
Agent Memory & Coordination
AI agents forget everything when the session ends. It is one of the central unsolved problems in applied AI right now. We are active in this space — testing persistent memory architectures, cross-agent coordination, and systems that know what to forget as well as what to remember.
Retrieval & Reasoning
When AI gives wrong answers, the failure point is retrieval 73% of the time — not the language model. We benchmark hybrid retrieval: dense vector search, sparse keyword matching, graph-augmented retrieval, and multi-stage reranking. The difference between sounding right and being right starts here.
Engineers Who Research
Our R&D is not a slide deck. It is engineers who read the papers, run the experiments, and ship what works. The frontier moves every week. Staying current is not optional — it is the job.