Arya.ai

What is Arya.ai?

Arya.ai is an Indian enterprise AI company that sells pre-trained models, an API gateway and model monitoring tools to banks, insurers and lenders. Its flagship platform, Apex, offers more than 100 APIs grouped into onboarding, digitisation, generative, predictive and computer vision categories.

Developers subscribe to individual APIs, send requests with a token and pay per successful call through a credit system, while larger institutions can run the same models on their own servers. Arya.ai’s Apex page claims average accuracy above 95%, a 99% API success rate and more than 300 million API calls a year; these are company figures rather than independent benchmarks. Outputs such as credit summaries or fraud flags support staff decisions and do not replace the lender’s or insurer’s own judgement.

The business trades as Lithasa Technologies Pvt. Ltd. and was founded in 2013 by Vinay Kumar and Deekshith Marla. In April 2024 Aurionpro Solutions bought a 67% stake, and Arya.ai says it still operates independently. A February 2025 press release repositioned Apex as a toolkit for building AI agents, and the 2026 site lists an enterprise AI operating system, Infinity OS, as coming soon. Customer logos on the homepage include ICICI Lombard, Axis Bank and TATA AIG.

Key Features

The Apex catalogue of more than 100 finance-ready APIs is the centrepiece, with Cred AI and Nexus extending it into SME underwriting and API traffic control.

• Apex API catalogue: Apex groups its pre-trained models into onboarding, digitisation, generative, predictive and computer vision sets. Examples include invoice extraction, resume parsing, QR code reading, signature detection and audio analysis, each called through its own REST endpoint.
• Onboarding and KYC: Onboarding APIs extract data from identity documents and check that the applicant matches them. Face verification and liveness detection compare a selfie with the ID photo and confirm a live person is present, cutting manual review in account opening.
• Fraud detection: Document fraud detection flags edited or tampered files, and a separate API screens images for deepfaked faces. The February 2025 Apex release also describes URL and email scanning for phishing attempts.
• Cred AI: Cred AI reads bank statements supplied as PDFs, scanned images or CSV files, including multi-bank and multi-account uploads. It returns true revenue breakdowns, balance forecasts, fraud flags and case summaries that cite the transactions behind each insight.
• Nexus gateway: Nexus is an API gateway that routes, rate-limits and logs traffic between applications and backend models. It offers role-based access control, encryption in transit and deployment on-premise, in the cloud, on Kubernetes or in serverless set-ups.
• AryaXAI: AryaXAI monitors machine learning models in production and explains individual decisions. It is aimed at risk and compliance teams who must show why a model approved or declined a case during an audit.

Pros

Finance-specific models are Arya.ai’s strongest argument, because KYC, statement analysis and fraud checks arrive pre-trained rather than requiring an in-house data science project.

• Built for regulated finance: The models target real banking and insurance jobs such as claims processing, KYC and SME underwriting. Logos from ICICI Lombard, Axis Bank and TATA AIG on the homepage suggest the tools have run inside large institutions.
• Quick to trial: Apex lists zero set-up costs and token-based REST calls that slot into existing systems. A developer can test an API on a sample file the same day they sign up, before any sales conversation.
• Strong privacy stance: Arya.ai states that submitted data is never stored and that it holds ISO/IEC 27001:2022 certification and GDPR compliance. For banks handling identity documents, this shortens the vendor-risk review needed before a pilot.
• Flexible hosting: Products can run in the cloud, on-premise, in a private VPC or as a hybrid. Institutions with strict data residency rules can keep sensitive records inside their own network instead of sending them to a shared service.
• Explainable outputs: Cred AI cites the transactions and periods behind each finding, and AryaXAI explains model decisions. Credit officers can check the reasoning rather than trusting a bare score, which matters when a decision is challenged.

Cons

Unpublished pricing is Arya.ai’s main weakness, since neither the credit rate per call nor any enterprise product price appears on its public pages.

• Hidden rates: The site describes pay-as-you-go credits but gives no price per call. Budgeting a pilot therefore needs a sales conversation, which slows small fintech teams comparing several vendors.
• Demo-first sales: Cred AI, Nexus, AryaXAI and on-premise installs all begin with a demo request. Teams wanting a self-serve plan beyond the trial calls may find the route to production slow.
• Few independent reviews: Independent user reviews on directories and review sites remain scarce. Headline figures such as 95%+ accuracy and a 99% success rate come from Arya.ai itself, so test them on your own documents.
• Developer skills needed: Apex is an API product with no business-user interface or mobile app. Engineers must wire responses into onboarding flows, case systems or dashboards before front-line staff see any benefit.
• Narrow focus: The catalogue centres on banking, insurance and lending workflows. Teams outside regulated finance may get better value from general services such as Amazon Textract or Google Document AI.

Who is Using Arya.ai?

Banks, insurers and SME lenders form Arya.ai’s core market, while fintech developers call Apex to add verification and document reading to their own products.

• Banks: Retail and commercial banks apply the onboarding APIs to account opening and KYC checks. Face verification and liveness detection reduce the number of applications needing manual review.
• Insurers: Claims teams use document extraction and fraud detection to speed up settlement. One case on the Arya.ai site reports claim processing falling from 60 minutes to under a minute.
• SME lenders: Credit teams run Cred AI over bank statements to produce cited case summaries. Final lending decisions stay with the lender, and the tool supplies evidence rather than approvals.
• Fintech developers: Product teams call Apex to add identity checks, invoice reading or deepfake screening to their apps. The free trial calls let them measure accuracy before buying credits.

Pricing

Arya.ai bills Apex per successful API call through prepaid credits after free trial calls, and it publishes no rates (official site, checked October 2026).

One directory says no trial exists, which conflicts with the official FAQ and signup page.

Disclaimer: request a written rate card with volume tiers before you build Arya.ai calls into a production workflow.

What Makes Arya.ai Unique?

Arya.ai bundles finance-specific models with its own API gateway and explainability layer, so one vendor covers inference, traffic control and audit evidence.

Generic AI marketplaces offer broad vision and language models and leave compliance to the buyer. Arya.ai starts from regulated tasks such as KYC, document fraud and SME underwriting, cites the data behind each Cred AI insight and lets the whole stack run on-premise, which suits institutions that cannot send customer records to a shared cloud.

Compatibilities and Integrations

Arya.ai connects through token-authenticated REST APIs, and its products deploy in the cloud, on-premise, in a private VPC or on Kubernetes.

• Platform: Web dashboard and documentation with REST APIs; there is no mobile app.
• Deployment: Cloud, on-premise, hybrid and private VPC, with Nexus also supporting Kubernetes and serverless set-ups.
• Inputs: Cred AI accepts PDF, scanned image and CSV bank statements, including multi-bank uploads.
• Security: ISO/IEC 27001:2022 certification and GDPR compliance claimed, plus role-based access in Nexus.
• Monitoring: A public status page tracks API uptime, and Nexus logs every call for review.

Arya.ai Tutorials

Testing Apex needs a work email, one API subscription and a sample document, and these six steps take you to a first result.

1. Sign up with a work email to receive the larger corporate trial allowance.
2. Browse the Apex catalogue and subscribe to one API, such as KYC data extraction.
3. Copy your API token from the documentation section.
4. Send a sample request with the token in the header and a test file in the body.
5. Compare the responses with manual checks on a small batch of your own documents.
6. Buy credits for self-serve use, or book a demo for Cred AI, Nexus or on-premise options.

How We Rated It

A 3.8 overall reflects strong finance-specific models and privacy claims, held back by unpublished pricing and limited public support resources.

Summary

Arya.ai suits banks, insurers and fintech teams that want specialist AI for onboarding, fraud and credit checks without training their own models. Its on-premise options and stated no-storage policy make it easier to clear through vendor-risk reviews than many general AI services. The main limitation is opaque pricing, which makes budgeting hard before a sales call. Treat its outputs as decision support, with final credit and claims decisions left to qualified staff. Use the work-email trial to test accuracy on your own documents before buying credits.