DeepFile
A million-token document co-pilot for lawyers, clinicians, and researchers who need to ask natural-language questions across an entire case file, patient history, or literature review and get citation-grade answers.
Legal, medical, and research professionals drowning in long-form records
- Whole-corpus Q&A: drop in 500K+ pages of filings, charts, deposition transcripts, or journal PDFs and chat with the whole thing
- Citation-grade source panel: every answer links back to the exact page and passage it came from
- Cross-document timeline builder: "show me every mention of drug X across this patient's records"
- Redaction and privilege-aware mode for sensitive legal and clinical material
New GPU architectures like MI450 are finally making million-token agentic inference affordable, unlocking AI tools that previously choked on real-world document volume.
Strong, multi-vertical demand: legal AI spending is established ($150-2,000+/seat/mo), clinical AI is the second-largest enterprise AI category at $600M+ in ambient docs, and Elicit reports 2M+ researchers using AI literature tools.Legal AI Pricing 2026: Harvey vs CoCounsel vs Clio (Real $) ↗Medical AI Tools Landscape 2026: Abridge, Hippocratic, Nuance DAX, Glass Health ↗Pricing | Elicit: The AI Research Assistant ↗
Extremely crowded across all three verticals: Harvey, CoCounsel, Lexis+ Protege, Westlaw Precision, Spellbook, Clio Duo in legal; Glass Health, Hippocratic, Abridge, Nuance DAX in clinical; Elicit, Consensus, SciSpace in research. Incumbents already bundle long-context features.Best AI Legal Tools in 2026: Harvey AI vs CoCounsel vs Lexis+ Protege ↗Medical AI Tools Landscape 2026 ↗
Clear willingness to pay exists (Harvey ~$1-2K/seat/mo, CoCounsel bundled at $150-400+/mo), but distribution is locked by incumbents with deep legal/medical content moats and enterprise sales teams, making monetization for a new entrant difficult.Legal AI Pricing: Complete 2026 Comparison ↗
Long-context is a durable trend (Llama 4 Scout at 10M tokens, Gemini 1M, etc.), but it is becoming commodity model capability rather than a defensible product feature; incumbents are rapidly adding million-token capabilities.The 10-Million-Token Breakthrough: What Legal Teams Can Actually Do With Llama 4's Long Context ↗
Building a long-context doc QA wrapper is technically tractable with existing models/APIs, but the MI450 angle is misleading — MI450 capacity is committed to OpenAI/Meta/Oracle hyperscalers for 2026, not accessible to startups; real challenge is ingestion, citation accuracy, and domain-specific guardrails.AMD and OpenAI Announce Strategic Partnership to Deploy 6 Gigawatts of AMD GPUs ↗