Accelerators

Ten production-ready accelerators. Governed from day one.

An accelerator is a proven pattern of agents, integrations, and governance controls for a recurring enterprise problem, configured to your data, systems, and policies rather than designed from scratch. Four vertical accelerators for industry-specific deployment. Six horizontal accelerators for cross-industry configuration.

Vertical · 4 accelerators

Industry-specific domain intelligence built in.

Built for industries where domain knowledge is integral to the solution: healthcare payment integrity, loyalty program reconciliation, supply chain dependency modeling, and banking operations intelligence.

Payment integrity and fraud intelligence

ArqFWA is a payment-integrity intelligence layer for healthcare payers. It correlates claims, provider, policy, and member signals to surface high-value fraud, waste, and abuse cases — each with the evidence trail investigators need to act and defend.

Built for Healthcare payers, TPAs, PBMs, and program-integrity teams

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Loyalty platform modernization

ArqLoyalty is a modern AI-governed loyalty engine adopted without migration risk: it runs in shadow beside your incumbent system, proves penny-for-penny parity every day, and cuts over one capability at a time on your timeline.

Built for Fuel & convenience, hospitality, malls, and any loyalty operator

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Supply chain and vendor risk intelligence

ArqLogistics watches your supplier and logistics dependency graph across contracts, ERP records, shipments, quality data, and external signals — and routes exposure-backed actions to the right owner before disruption becomes a business event.

Built for Energy, manufacturing, logistics, and procurement teams

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Banking operations and intelligent financial services

ArqBanker is an AI-native operations layer for banking institutions that automates underwriting, customer onboarding, AML surveillance, and regulatory reporting — with explainable reasoning on every decision.

Built for Retail banks, credit unions, digital lenders, neo-banks, and insurance carriers

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Horizontal · 6 accelerators

Cross-industry problem patterns, configured to your context.

Built for problems every enterprise shares — forecasting, service management, data quality, competitive pricing, security operations, and data observability — configured to your data and operating context.

Demand and cash flow forecasting

ArqForecast is a production-ready AI forecasting accelerator: an ensemble of 20+ models spanning time series, multivariate, and deep learning architectures, dynamically selecting the best combination for your data and deployed in 15 to 30 days.

Built for Retail, manufacturing, finance, operations, and supply chain teams

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Agentic ticket and service management

ArqSupport is a multi-agent platform for intelligent ticket triage, automated resolution, and proactive SLA management — resolving L1 tickets autonomously, assisting L2 with drafts and context, and escalating L3 with full context assembled.

Built for IT operations, shared services, HR ops, finance ops, and any support team

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Data quality monitoring and remediation

ArqDataQ is a multi-agent data quality system that monitors pipelines in real time, classifies issues by type and severity, identifies root causes, and remediates known issue patterns autonomously — before end users ever see a problem.

Built for Data engineering teams, analytics teams, CDOs, and any data-dependent enterprise

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Competitive market intelligence and dynamic pricing

ArqVantage monitors competitor SKUs in real time, interprets why prices moved using LLM reasoning, and reprices within governance guardrails — with MAP compliance enforced automatically and a full audit trail on every pricing decision.

Built for E-commerce brands, manufacturers, revenue management teams, and marketplace sellers

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Security operations and incident intelligence

ArqSecOps is a SecOps intelligence layer that compresses time-to-context: it enriches alerts, correlates incidents, drafts audit-ready summaries, recommends response steps, and captures the evidence GRC needs — on top of your existing security stack.

Built for Cybersecurity teams, SecOps, GRC, risk operations, and any regulated industry

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AI-native data observability and pipeline intelligence

ArqEye is an AI-native data observability platform that monitors the health, freshness, quality, and lineage of data assets continuously — detecting anomalies at ingestion, tracing failures to their origin, and enforcing SLAs per data product.

Built for Data engineering, analytics engineering, BI teams, CDOs, and data-intensive SaaS

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Governance commitment

No black boxes. Governance designed in, not bolted on.

Every accelerator produces encrypted, audit-ready proof on every agent action. Every decision, recommendation, or autonomous action carries the trigger, the reasoning, the data inputs, and the outcome in a structured, persistent audit trail — a foundational requirement of the agent architecture, not an afterthought.

FAQ

What is an ArqAI accelerator?

An ArqAI accelerator is a pre-built, production-proven pattern of agents, integrations, governance controls, and operational logic for a recurring enterprise problem, configured to fit your data, systems, policies, and operating metrics. Deployment is measured in weeks rather than quarters.

What is the difference between vertical and horizontal accelerators?

Vertical accelerators are built for a specific industry where domain knowledge is integral: ArqFWA for healthcare payment integrity, ArqLoyalty for loyalty platform modernization, ArqLogistics for supply chain risk, and ArqBanker for banking operations. Horizontal accelerators solve problems that appear across industries: ArqForecast (forecasting), ArqSupport (ticket management), ArqDataQ (data quality), ArqVantage (competitive pricing), ArqSecOps (security operations), and ArqEye (data observability).

Put an accelerator to work.

Start with a fit check. We compare your workflow, data, and controls against the accelerator before recommending a rollout path — and show where bespoke engineering is the better answer.