Think fast.
LLM intelligence, compiled.
sparkient.ai
Fast (< 1ms) but brittle. Can't handle nuance. Break on edge cases.
Better, but requires an ML team, months of labelled data, and constant maintenance.
Smart but slow — 1‑3 seconds per call. At scale, $250‑$1,000/day.
Describe the decision your app needs
The LLM teaches a fast model offline
Compiled model runs in production — no LLM calls
The LLM is the teacher, not the runtime.
Foundation models can label with human-quality judgment. This wasn't possible two years ago.
Content moderation, fraud detection, agent guardrails. Demand for real-time intelligent decisions is exploding.
Per-request pricing breaks at volume. Companies hitting $5K–$30K/month on classification alone.
POST api.sparkient.ai/api/v1/decide
{
"decision_type": "content-moderation",
"input": { "text": "Buy followers cheap!" }
}
→ 12ms
{
"decision": "restrict",
"confidence": 0.94,
"reason_codes": ["spam_commercial"],
"latency_ms": 12
}
Support Triage
96.2% acc · 42ms
Marketplace
94.3% acc · 33ms
Content Moderation
91.5% acc · 41ms
Gaming Chat
91.0% acc · 34ms
All trained on noisy, imbalanced data. Full methodology at sparkient.ai
Rules Engines
Fast but rigid
Sparkient
Fast & intelligent
LLM APIs
Intelligent but slow
LLM APIs
Sparkient
Cost model
Per-request
Fixed monthly
50K decisions/day
$250–$1,000/day
From $199/mo
LLM APIs
Sparkient
Starter
$199/mo
Growth
$599/mo
Scale
$1,999/mo
SEIS eligible — 50% income tax relief for UK angel investors
Founder & CEO
Scaled a national franchise
CEO of Geek Retreat. Grew from 4 to 64 locations across the UK. £20M annual revenue.
Built latency-critical systems
Helix: high-frequency crypto arbitrage platform. Compiled ML models making decisions in ~50ms.
Solo-built Sparkient end-to-end
Full production platform: API, ML pipeline, dashboard, billing, edge SDK, MCP server. Deployed and hardened.
Take slow intelligence and make it fast. — Sparkient
First customers
Pilot users for traction and feedback.
Advisory network
Mentorship and GTM strategy expertise.
Pre-seed round
Capital to scale what's working.
If any of this resonates, I'd love to continue the conversation.
peter@sparkient.ai
sparkient.ai