Minctrl is an AI-native BPM platform. AI agents execute your regulated business processes end-to-end — and a governance layer decides exactly when a human still signs off: risk-tiered gates, a panel of compliance judges, calibrated confidence and a tamper-evident audit trail.
LangGraph state machine — 9 fixed stages with checkpoints, security gates, and a human-readable audit trail. Every run follows the same proven process.
Separate agent teams per vertical. Fintech agents know FIX, MiFID, pre-trade risk. Crypto agents know reentrancy, oracles, MEV. Not templates — specialists.
Every risky step is a gate. A tier resolver routes it — low-risk reversible work can auto-clear, medium goes to a panel of compliance judges, irreversible always waits for a human. Calibrated confidence and a tamper-evident audit trail on every decision.
A LangGraph state machine coordinates every agent through 9 fixed stages with built-in checkpoints. No black box — full agent log, cost breakdown and audit trail for every run.
Detect pipeline type, load domain config, bootstrap state
Deep reasoning: architecture debate, security review, meta-critique
Specialists per vertical — fintech, crypto, AI, infrastructure
High-frequency tasks: DevOps config, cost tracking, formatting
Fintech is Minctrl's flagship domain — each pipeline ships 5 specialist agents, 6–13 mandatory compliance frameworks, a curated stack and 3 knowledge seeds, built end-to-end in ~30 minutes. The same agents construct governed process flows for 25+ regulated verticals — prior-auth, tax, AML, payroll, RCM and more.
Retail banking, capital markets, KYC platforms
Stocks, fractional shares & FIX execution — built end-to-end
Ledger, IBAN accounts, SEPA payments, AML6 monitoring
Banking-as-a-Service: multi-tenant, sponsor bank rails, ISO20022
Pro trading terminal: order book, charts, sub-50ms latency
Quant platform: signals, backtest, portfolio risk, prime brokerage
KYC/AML platform: document OCR, biometric liveness, FATF compliance
Automated wealth: MPT allocation, rebalancing, MiFID suitability
AI-native bank where AI agents are first-class customers (β)
Bridges between fintech and legacy banks / telecoms — added 2026-05
ISO 20022 + SWIFT MT/MX + batch settlement — Temenos/Mambu/Finacle middleware
PSD2/PSD3 AISP+PISP across UK OB / Berlin Group / FDX with FAPI security
Stripe Treasury class — white-label finance for marketplaces & gig platforms
M-Pesa / MoMo / Orange — telecom-led wallet for emerging markets
Direct Carrier Billing — Boku / Fortumo / Bango aggregators, voucher distribution
The ai-agent-bank pipeline ships a full design including DID-based agent identity, agentic KYC, stablecoin payment rails, and multi-sig governance — with a mandatory EU AI Act + DORA compliance pack generated automatically. Preempts Catena Labs positioning.
W3C DID + Verifiable Credentials for every AI agent. did:web primary, eIDAS 2.0 wallet.
Tiered onboarding: model fingerprint → capability proofs → behavioural monitoring.
USDC / EURe stablecoin + CBDC adapter + SWIFT fallback. IVMS101 Travel Rule built in.
6 AI-specific scenarios: prompt injection, runaway loop, hallucination, capability creep, model drift, supply-chain.
m-of-n threshold-sig over agent decisions. Timelock. Append-only audit log. Kill-switch.
Mandatory compliance review: Articles 6, 9–15. DORA ICT risk. MiCA. AML5/6. Evidence pack generated.
Minctrl scores every gate by blast radius and reversibility, then routes it: low-risk reversible steps can clear automatically, medium-risk go to a panel of compliance judges scored by meta-critic, and irreversible steps always wait for a human. A tamper-evident audit trail records who decided what. Security and compliance gates stay mandatory for regulated work.
Nine agent stages. A human reviewer approves between each one. Security and Compliance gates are mandatory for regulated builds and cannot be skipped.
Six integrated views into a running pipeline — console, code, cost, board, wiki, analytics.


Project list + create workflow.

Auto-populated tickets per gate.

Auto-generated docs across runs.
Six integrated modules, built around the agent pipeline. Each one kept in sync with the live run state.
Live workflow status · recent runs · quick switcher
Pipeline type · goal & config · run history per project
Execution graph · streaming console · artifacts
Auto-populated by domain agents · status tracking
PRD · arch · API docs · data models · always synced
Per-agent cost · token usage · traditional-team compare
Three tiers — start free, pay only when AI ships actual code. Enterprise gets bespoke compliance frameworks and on-prem deploy.
Explore what AI engineering can ship. Bring your own LLM key.
Avg cost per pipeline: $0.50–$2 in LLM tokens · Free tier covers your first 30 builds