Localized LLM viability

Verdict

What Mark can say this week

Enterprises already buy seats and tokens under strong privacy contracts. The break is high-volume ops data: control of the intelligence environment, plus economics that only work when local utilization and model quality hold. Palantir proves the governed-ops market is thick. Cosmic wins on data gravity and measured unit economics — shown in paid POCs — not on training fear. Tuesday narrative

Market need — what people buy

Enterprises buy two meters, often both. Token-savings pitches only land when the pain is usage bills or caps — not seat fees alone. Many still see the AI bill but not the unit cost (Deloitte 2026: 71% track total inference spend; 44% track per-unit cost).

Demand triggers that survive enterprise privacy products

• Cost at volume (agents, RAG loops, always-on ops copilots)
• Latency on site / plant / network edge
• OT / air-gap / jurisdiction that ZDR does not solve
• Need to combine many first-party streams into one actionable picture (Cosmic’s stated shtick)

Survey McKinsey State of AI 2026 · Menlo 2025 genAI spend (~$37B) · Deloitte privacy / residency

Data centers first — three buyers

Mark’s priority. Not one market. Cosmic can get paid more than once on the same megawatts.

Other priority verticals (thin until DC holds)

Economics — three ledgers, not one

Confusing these three is how decks get ripped apart.

When localization wins on dollars

• Steady high utilization (idle GPUs kill the case — self-host bills by the hour; Bedrock-style APIs bill ~$0 idle)
• A smaller / domain model is good enough on eval
• Orchestration, security, and staffing overhead do not erase the gap

When localization wins on strategy even if public is cheaper

• Air-gap / OT isolation / jurisdiction requirements
• Buyer will not put prompts, embeddings, or logs in a third-party path

Displacement scenarios — labeled only

Scenario Not Cosmic forecasts. Do not put these in a customer deck as measured.

Paid public usage down ≠ total inference down. Retrieval, routing, retries, eval, and agent loops can raise total tokens while the public bill falls. Sell lower public bill and less egress — not “fewer tokens in the universe.”

Pricing structures that fit

Thesis: hybrid platform + metered AI + optional device/outcome, discovered in a paid POC — not one list price for every vertical.

Pike proposal · Assurant draft · BAIT execution / users unconfirmed

Palantir — compete honestly

AIP has twelve documented capability layers. Layer 1 is secure LLM access (commercial + open). The rest is observability, context engineering, Ontology, vector/compute/tools, security, agents, automation. Customers can bring their own models, including self-hosted on-prem / air-gapped compute modules.

Commercial DC / construction names (McCarthy, Cavanagh, Chain Reaction / Nscale / CenterPoint) are covered in the separate Palantir commercial note — use that for diligence, not slogans.

Sovereignty — past “not used for training”

Cosmic’s sovereignty pitch must name: processing location, jurisdiction, access, keys, prompts, outputs, embeddings, retrieval stores, logs, fine-tunes, retention, backups, support access, subprocessors, deletion, audit — and air-gap only if product can deliver.

Evidence gates before “done”

Per Keli: Tuesday is preliminary + iterate. “Done” means these questions are listed and owned — not that sales claims are final.

1. Relativity Engine — one paragraph: what it is, what it is not (vs Ontology / RAG / entity resolution), what a buyer sees.
2. Models — which power engine vs dashboard; local vs frontier; eval on Cosmic tasks.
3. Routing — design target mix from a real POC; never invent % for decks.
4. COGS — fully loaded local + frontier pass-through vs Pike-style customer price; confirm ~80% margin math.
5. Deploy — on-prem / air-gap: real, planned, or out of scope.
6. Ledger / BFT — customer-visible product or plumbing.
7. Buyer — which data-center payer Mark’s meeting targets this week.