Every levelhas a personality.
MIB (Market Intelligence Base) is a persistent AI knowledge base that learns the behaviour of each price level and turns it into filtered MT5 / exchange-API trading signals.
MIB agents don't analyse from scratch — they remember. Each price level accumulates a statistically proven behavioural pattern, compressed to ~98 tokens via 1-bit semantic graph. Powered by Claude Opus 4.7. Works with MT5 or any exchange API.
Three-Layer Intelligence
Raw market events flow through an AI-managed knowledge layer and emerge as statistically validated signals — fully automated, fully auditable.
Raw Intelligence
MT5 or exchange API streams approach events as structured markdown the instant price touches a level. Files are never modified.
Level Intelligence
Claude Opus 4.7 synthesises every touch into a living wiki page. After 5+ reactions, the level gets a Personality.
Actionable Signals
High-confidence forecasts crystallise into executable signals. Only absorption_rate ≥ 65% + R:R ≥ 2.0 reach MT5 or exchange API.
Four Core Operations
The agent runs autonomously — ingesting raw data, generating forecasts, filling reactions, and auditing consistency. No human in the loop until a signal is confirmed.
## [2026-04-08 14:00] INGEST Level-1.08450 | raw: 2026-04-08_14-00_Level-1.08450_approach.md → wiki page exists: YES (touches: 3) → touches_with
What sets MIB apart
Every component is measurable. No black-box decisions — every pattern has a numerator, denominator, and percentage.
Personality Synthesis
After 5+ reactions, Claude Opus 4.7 synthesises a statistically proven behavioural pattern — not a heuristic, a formula.
BitQuant Compression
1-bit semantic graph extracts knowledge chains and encodes the entire wiki page into ~100 tokens for efficient API calls.
Adaptive Signal Filter
Only levels with absorption_rate ≥ 65%, twr ≥ 5, and R:R ≥ 2.0 reach execution. The filter adapts as the KB matures.
Self-Auditing LINT
Daily LLM audit detects contradictions between Personality descriptions and actual statistics — flags under_review levels.
BitQuant compression — verified
Benchmarked across real production knowledge bases. Opus 4.7 judged semantic equivalence between full and compressed contexts.
Context compression that shouldn't work — but does
97% token reduction with zero reasoning quality loss sounds like a contradiction. The key insight: a wiki page has massive redundancy — the semantic structure can be expressed as a sparse binary graph, not a wall of prose.
Structured markdown: frontmatter, history table, pattern section, context
Domain-aware parser extracts trading concept relationships
Each concept connection: 0 or 1 — relevant or not relevant to query
Compressed context delivered to Claude API instead of full page
Binary is valid when the question is binary
Traditional RAG uses float32 embeddings — 32 bits per dimension — to score cosine similarity between chunks. This is designed for "how similar is this document to the query?" — a continuous question.
BitQuant asks a different question: "Does Pattern X relate to History Entry Y in the context of this specific query?" That question is genuinely binary. No gradient needed. No cosine distance needed.
Each semantic relationship in the knowledge graph is quantized to 1 bit: relevant (1) or not (0). The resulting sparse graph is orders of magnitude smaller than any embedding-based representation — with no loss of structured reasoning quality.
GRAPH LEGEND
Rate: 9/11 = 81.8%
| — | Traditional RAG | BitQuant |
|---|---|---|
| Representation | float32 embeddings (1536 dims) | 1-bit graph edges |
| Storage / level | ~24 KB | ~0.6 KB |
| Tokens / query | 4,263 tokens | 98 tokens |
| Query type | "How similar?" — continuous | "Is related?" — binary |
| Reasoning quality | Loses structured context | Preserves full structure |
| Speed | Dense vector search | Sparse BFS traversal |
| Semantic equivalence | — | Verified 100% (85/85) |
Measured across 85+ profiled levels
Claude Opus 4.7 judged semantic equivalence between full-page and compressed contexts. Both queries return identical pattern matches and confidence scores.
Any domain with structured persistent knowledge
BitQuant's semantic chain extraction is domain-agnostic. The parser learns the terminology — the compression mechanics are universal.
Run the Agent
Switch between EUR/USD and Gold. Every operation runs the exact same pipeline used in production — only the data changes.
Built by a Trader, for Traders
14 years in markets. 4 years in AI. One mission: give solo traders the same level intelligence institutional desks use internally.
Anton Serozhkin
14 years studying financial markets — from manual trading to teaching algorithmic strategies. The last 4 years: deep into AI, building indicators and trading algorithms that see what human traders miss. The system operates via MT5 bridge and direct exchange APIs (Bybit, Binance) for multi-venue execution.
Institutional desks have used price-level behavioral models for years — internally. Solo traders get emotion and intuition. MIB v2 changes that: a persistent AI knowledge base that accumulates the statistical "personality" of every price level, eliminating the human factor where it's weakest.
Live on real capital · EURUSD+ (Bybit) · XAUUSD+ (Bybit/Binance) · Signal filter active
in financial markets
in AI development
tracked in knowledge base
autonomous monitoring
The core insight
MIB's mechanics can analyze any data expressible as price over time — gold, equities, indices, crypto. The knowledge base architecture is instrument-agnostic. This is the foundation for multi-market expansion.
Current stage
Live on real capital. Signal filter active — validated signals with absorption rate ≥ 65% and R:R ≥ 2.0 are delivered to MT5 bridge or exchange API (Bybit, Binance) for execution. Pattern recognition confirmed across multiple market sessions.
12+ Monetization Paths
Starting with pay-per-query and SaaS subscriptions. Expanding to multi-asset, institutional, and white-label as the knowledge base matures.
Pay-per-query analytics
From $1/asset/day — instant access to level intelligence
Tiered SaaS subscriptions
Solo trader → Team → Fund tiers
Bring-your-own-strategy platform
User connects API keys, uploads strategy, MIB executes with its mechanics
White-label API for brokers
Broker embeds level intelligence into their platform
Signal subscription
Validated high-confidence signals delivered to subscribers
Launch Roadmap
Live signal product
- ›Pay-per-query analytics ($1/asset/day)
- ›EURUSD+ · XAUUSD+ live
- ›Signal subscription launch
Multi-asset expansion
- ›Stocks, crypto, indices
- ›White-label API preview
- ›Institutional pilots
Platform scale
- ›Bring-your-own-strategy
- ›BitQuant API standalone
- ›Public launch
Join the Waitlist
MIB v2 is in live testing. Early access members get priority onboarding, direct line to the founder, and lifetime early-adopter pricing.
Priority onboarding
Personal setup call with the founder
Early-adopter pricing
Locked rate before public launch
Direct feedback channel
Shape the product roadmap
Multi-asset beta access
First to test new instruments as they launch
Strategy integration beta
Be first to connect your own strategy logic