DeltaStore
Solstice AI Studio  ·  Memory Infrastructure for Enterprise AI
Justin Meister
Founder & Chief Architect
[email protected]
solsticestudio.ai/deltastore
Most AI systems are quietly drowning in their own memory. Every agent state, every reasoning trace, every branching simulation path — stored in full, over and over again. We built a fundamentally different approach: store changes, not state. The result is 25×–593× compression in production, with audit trails built in by default — not bolted on.
Production Compression — Live Systems
System Traditional Delta Savings
Convergence (100k perspectives)1 GB10 MB100×
Time-Travel Debug (1k snapshots)10 GB110 MB91×
RL Replay — Atari28 GB228 MB123×
RL Replay — Minecraft100 GB500 MB200×
Deep Branch Tree (factor 4, depth 5)1,365 MB2.3 MB593×
Redis Cache Layer1 GB10 MB100×
Why It Works — The Architecture

Instead of full snapshots, Delta records only the diff between states — the minimal set of changes to transform one state into the next. Periodic keyframes ensure fast reconstruction.

Reconstruction: O(d) complexity — proportional to reasoning depth only, not total storage. Worst-case: 100 delta replays from the nearest keyframe. Sub-millisecond.

593×
Peak Compression
O(d)
Reconstruction
14
Domain Modules
8
Live Systems

Domain modules: Healthcare formularies, RL replay buffers, vehicle telemetry, tax code versioning, quantum angle compression, adversarial strategy evolution, perspective synthesis, time-travel debugging.

Business Model — Two-Track Revenue
Track 1: Healthcare Vertical — Lead Motion

Product: DrugPriceChain — cryptographically auditable PBM pricing. Every markup, rebate, and spread recorded as a signed delta chain. Employer sees penny-by-penny where drug spend goes.

Buyer: Self-insured employers (5,000+ employees). 6,000 targets in the US. CFO / VP Benefits.

Why they buy: PBM audits cost $200k–$500k and happen every 3 years. DrugPriceChain is continuous, automatic, and a fraction of the cost. ROI is 3–7× in year one on recoverable spread alone.

Channel: Benefits consultants and TPAs — one TPA relationship = pipeline to 100+ employers.

  • ACV: $75k–$150k/year per employer
  • 18-month target: 100 customers = $10M ARR
  • 3-year target: 500 customers = $50M ARR
Track 2: AI Infrastructure Licensing — Scale Motion

Product: Delta Storage as a drop-in memory layer for enterprise AI stacks. Wraps agent state, RL replay buffers, and reasoning traces. No rearchitecting required.

Buyer: VP Engineering / CTO at companies running production AI agents. Financial services, logistics, healthcare, legal. Paying $50k–$500k/month in storage today.

Why they buy: Immediate storage cost reduction (25–200×) plus auditability built in — which their enterprise customers are beginning to require contractually.

Channel: Direct enterprise sales, AWS/Azure marketplace, AI framework integrations (LangChain, AutoGen).

  • ACV: $12k–$24k/year (usage-based, scales with agents)
  • 2-year target: 1,000 customers = $15M ARR
  • 4-year target: 5,000 customers = $75M ARR
Market
PBM / Drug Pricing Transparency$500B+
Self-insured employers spend $400B+ on prescription benefits annually with near-zero visibility into PBM fees and spread pricing
AI Infrastructure Storage$80B → $200B
Global AI infrastructure market growing 30%+ YoY. Storage is a primary cost center as agent systems scale to production
Regulatory Compliance Infrastructure$50B+
EU AI Act, FDA AI guidance, SEC AI rules — audit trails becoming legally mandated across healthcare, finance, and critical infrastructure
Moat
  • 14 domain-specific modules — each requires deep domain knowledge to build correctly. Healthcare formularies, RL buffers, vehicle telemetry, tax code versioning. Not replicable in 18 months.
  • Audit trail lock-in — once 3 years of employer drug history lives in DrugPriceChain, switching means losing the entire audit record.
  • Regulatory inevitability — auditability is moving from optional to legally required. Delta makes compliance a side effect, not a project.
  • No direct competitor — vector DBs store embeddings, MLflow tracks experiments, event sourcing frameworks are generic. Nobody is doing domain-specific delta compression for AI state at this abstraction level.
$3M
Seed Round
Pre-seed complete. Raising $3M seed to fund sales motion, first 3 enterprise hires, and TPA channel partnerships.
18 Mo.
To $10M ARR
100 healthcare customers via TPA channel. Proof of enterprise AI licensing model. Series A ready.
$100M
ARR Path
500 healthcare + 5,000 AI infrastructure customers by year 4. Dual-track compounding revenue with high retention in both verticals.