Four engines + industry solutions: AML, data governance, KYC, risk
Core EngineOne sentence to a working system in 60 seconds
Describe your business need in natural language and get a production-ready system in 60 seconds: database tables, CRUD APIs, admin UI, filtering, pagination, and validation—all at once. Traditionally a new business object takes 10-18 days with 4-5 people; with OMS it is one sentence, one minute, zero code. Includes a state-machine engine for lifecycle management, cross-object navigation, and built-in import/export.
Core EngineAsk your data questions, no SQL required
Connect a database and ask questions in natural language—no SQL, no analyst queue. The system understands your schema, generates and executes queries, and returns charts ready to read. Permissions, data masking, and audit are built in: people see what they should see, and every question leaves a trail. Business users self-serve reporting; IT stops drowning in ad-hoc requests.
Core EngineEvery model through one gateway, auto failover
A unified LLM gateway that lets every application on the platform share the same model capabilities: intelligent analysis, report generation, content understanding, and assisted review. Multi-model automatic failover keeps business running when a provider is slow or down. Prompts are versioned and centrally managed; usage is metered in one place. AI-assisted AML screening and due-diligence reports all run on this layer.
Core EngineWrite workflows as config, not code
Complex business workflows without writing code: extraction, cleansing, model batch runs, reports, notifications—composed like building blocks. Failed batches resume from checkpoints; every step reconciles. Heavy lifting like scheduling, parameter simulation, and AI-assisted review runs on it. Change a flow by editing config, never waiting on developers.
FlagshipCreate your business agent with one sentence
Describe your business task in one sentence—"analyze transactions for suspicious fund flows" or "QC this batch of medical records against every rule"—and AI proposes the domain, scenario, and tables within seconds. You confirm, the agent is generated, then verified by dual runs on real data with consistent conclusions before release. AI proposes; humans decide. Two agent archetypes (data-analysis and document-review) cover government, enterprise, education, and healthcare. 42 battle-tested agents out of the box; new customers swap rule packs, not code.
Enterprise agents that remember, benchmark, and stay governed
Agents as production digital workers, not chat toys. Cross-session memory remembers past investigation conclusions; a benchmark suite makes success rates measurable; tool calls are gated by role with full audit trail; a sandbox caps resource usage; every agent's calls and token usage are metered separately. Fully private deployment.
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NEW · 62 verified scenarios14 agents across the full AML chain, querying live databases autonomously
Say it once, the agent investigates: alert triage, sanctions screening, UBO tracing, fund-network graphs, report reconciliation, rating migration — 14 AML agents covering monitor-triage-report-review. Each agent queries live databases (46M transactions / 780K alerts / 2.86M rating tracks at bank scale) and files structured, auditable conclusions with real numbers.
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Triage workbench, agent legion, and compliance loop—one system redefines AML operations
A next-generation AML operations platform built around AI-assisted triage with human sign-off. Five role workbenches cover the full alert lifecycle; 14 AML agents collaborate like staff. Triage replay makes every AI reasoning step reviewable; coverage matrix and regulation ledger turn compliance into daily routine. Proven on bank-scale data: 46M transactions, 780K alerts.
ExtensionFull-database relocation without downtime
Heterogeneous database relocation: full-database migration across Oracle, MySQL, and PostgreSQL with automatic schema translation, batched data movement, and initial-plus-incremental continuity. Dialect type differences are adapted automatically; row counts and content reconcile before and after. When replacing a legacy system, historical data moves over in one pass—without stopping the business.
ExtensionSanctions screening: recall first, fewer false positives
A multi-algorithm entity matching engine built for sanctions screening, KYC, and watchlist monitoring. Exact, transliteration, and fuzzy recall run in parallel and complement each other—maximize recall first, then reduce false positives. Validated at 100M-scale lists with 10K-scale throughput; every match carries explainable evidence for regulatory audit trails.
FlagshipInternal control: policy to remediation, closed loop
Turns the whole internal-control chain—policy, risk, controls, inspection, findings, remediation, assessment, reporting—into a configurable delivery: an in-database check engine runs 71 baseline rules (covering all 18 application guidelines) plus industry packs for government, enterprise, education and healthcare, each hit carrying its regulatory clause and source evidence. 33 storage-layer triggers (across 20 core tables, via 5 trigger functions) enforce segregation of duties, one-way state machines and audit trails at the storage layer (even TRUNCATE leaves a trace), with audit events landing in an immutable, undeletable ic_audit_log. Onboarding a new customer means swapping rule packs and mapping their data to ic_ business tables, not writing code; the management console and scheduled inspections are in production, with tenants isolated per database.
深耕金融行業場景，開箱即用的智慧化方案
Alert triage, AI SAR drafting, sanctions screening, large-value reports and regulatory message validation.
Metadata discovery, 7-type quality checks, lineage tracing and metric reconciliation.
Declaratively orchestrate cross-system flows: data ingestion, AI processing, result persistence, notifications — zero-code with resume-from-checkpoint.
From product modeling to remarketing: seven links in one chain, editable by chat.
Topic bank, batch production, scheduled multi-platform publishing, data feedback, AI pattern-finding.
從四驅引擎釋出到行業場景落地——每一次迭代都是可驗證的能力躍遷
PG foundation upgraded to PostGIS + TimescaleDB + pgvector; MQTT real-time mapping lands in the kernel connector layer; a smart-building operations industry pack ships out of the box.
Simulate indicator impact before any threshold change (P90 data-anchored calibration); the knowledge-base industry layer ships with packs (regulations / cases / risk signals) out of the box.
Any OMS business object gets a public intake form; creative assets go generate→upload→ad-publish in one pipeline.
Alert triage, SAR drafting, watchlist screening, large-value reports, six-dimension regulatory message validation — AI staff for three compliance roles.
Capabilities unified; one sentence yields a complete business system — data structures, permissions, sample data — cutting delivery from weeks to minutes.
Describe your industry & products → AI generates a full branded site: copy, palette, layout, SEO, with an automatic quality gate.
OMS modeling · DBChat NL-query · Cortex understanding · Loom orchestration — an ontology-driven AI-native enterprise foundation.
每個引擎一個殺手場景，30 秒感知價值
企業級能力棧 + 54 個行業模板。從模板匯入到AI建模，全鏈路零程式碼。
透明的價格，按需選擇
從零售門店到醫療器械製造，從物流倉儲到農業種植。選行業 → 一鍵匯入 → 即開即用。
不講概念，只放實彈。每個 demo 都可在演示環境現場復跑。
從資料隔離到許可權控制，從操作審計到合規保障——企業級安全不是可選項。
每個企業獨立資料空間，租戶間零交叉，許可權邊界清晰。
角色許可權+功能許可權+資料許可權，統一認證統一審計。
所有操作留痕，資料變更可追溯，滿足監管檢查要求。
完整系統部署在企業內網，資料不出行，滿足金融級合規要求。
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