Fast, cheap, effective finetuning; readily hotswappable for endless and near-instant model customisation
Finetuning traditionally requires hours of compute, careful dataset curation, and per-model costs that scale poorly. Our foundational research into intelligence at scale has enabled us to achieve the desired behavioural adaptation and corpora-grounding in minutes. The implications extend well beyond researcher personae:
Expert witness and advisory simulation: law firms and consultancies reconstructing the reasoning style of domain specialists for case preparation, deposition practice, or client-facing deliverables.
Institutional knowledge preservation: capturing the decision-making patterns of retiring executives, senior engineers, or investment professionals before they walk out the door.
Bespoke analyst personae for finance: ingesting a PM's investment memos, IC notes, and market commentary to produce an assistant that reasons in their voice, badly needed for training junior staff or stress-testing theses.
Technical sales and pre-sales engineering: adapting a model to speak fluently about a company's product, architecture, and competitive positioning without weeks of fine-tuning and prompt-wrangling.
Privacy and Data
All paper data is sourced from the public arXiv repository. Please note the system respects arXiv's rate limits (3 seconds between requests) so speaking to researchers with large outputs may take some time.