Saris AI is an enterprise AI company that builds agentic workflow automation for banks and credit unions. Its platform deploys AI agents to execute complex back-office tasks like lending, compliance checks, and document processing, integrating directly with existing banking systems rather than replacing them.
At a Glance
- What it does: Automates back-office workflows at banks and credit unions using agentic AI
- Target customers: Mid-size credit unions to large North American banks
- Key technology: Native desktop application with direct software bindings, not screenshot-based automation
- Funding: $28.8 million Series A led by 8VC, announced May 2026
- Founders: Danial Jameel, Alice Dinu, and James Dang, previously of Ready Education
- Claimed results: Up to 70% automation of lending tasks with 35% cost reductions
What Is Saris AI?
Saris AI is an artificial intelligence company focused on automating the back office of financial institutions. Founded in 2023, the company is dual-headquartered in San Francisco and Montreal .
The platform builds AI agents that handle non-customer-facing administrative work at banks and credit unions. This includes consumer lending, mortgage processing, commercial lending, compliance verification, and document handling .
Saris raised a $28.8 million Series A round in May 2026, led by 8VC, the venture firm founded by Palantir co-founder Joe Lonsdale . The round included participation from Audacious Ventures, Homebrew, Btech Consortium, and Service Ventures .
The company’s leadership team has prior startup experience. CEO Danial Jameel, along with co-founders Alice Dinu and James Dang, previously founded Oohlala Mobile, a Y Combinator-backed edtech startup that later became Ready Education .
The Problem Saris AI Addresses
The back office of most financial institutions has not kept pace with technological change. According to data cited by 8VC, approximately 700,000 back-office employees work across 8,300 banks and credit unions in the United States, representing $50 billion in salary spend .
A single mortgage lending process can involve 50 or more steps. These steps span document intake, insurance verification, compliance checks, and data validation across multiple systems. Many of these systems lack modern APIs, forcing staff to manually move data between disconnected applications .
Prior automation attempts relied on robotic process automation (RPA) tools that automate clicks. These approaches are brittle, break when interfaces change, and cannot handle the non-linear, multi-turn nature of complex lending workflows .
Saris positions itself as addressing this gap with agentic AI, a category of automation that uses AI agents to understand context, make decisions, and execute multi-step tasks with some autonomy.
How Saris AI Works
Saris AI operates through a native desktop application that runs alongside the software financial institutions already use. The company describes its approach as building direct bindings to banking systems rather than relying on screenshot-based computer-use agents .
This architectural choice matters for several reasons. Screenshot-based agents lock the user’s screen during execution and can fail unpredictably. Saris claims its system keeps the desktop fully usable while workflows run .
The platform orchestrates workflows end-to-end. When something fails mid-process, specialized self-healing agents diagnose the issue and resume from where the workflow stopped. If a downstream step reveals an upstream problem, the system loops back to address it and continues forward .
A concrete example from Saris’s own description illustrates the workflow. An AI agent can be tasked with collecting missing documents, validating information, identifying inconsistencies, requesting additional materials, and preparing a file for final human review .
Key Features
Agentic Workflow Automation. The core product deploys AI agents to execute lending, compliance, and operational workflows. The company claims automation of up to 70% of consumer, mortgage, and commercial lending tasks .
Native Desktop Integration. Saris operates through a desktop application with direct bindings to existing banking software. This reduces disruption to current systems and teams .
Self-Healing Execution. When a workflow step fails, specialized agents diagnose and resume the process. The system supports non-linear execution, looping back to fix upstream issues when needed .
Business User Configuration. Workflows are managed by business users without requiring IT or engineering involvement for routine configuration or troubleshooting .
Existing System Integration. The platform integrates with partners including Fiserv, Encompass, and MeridianLink, allowing institutions to avoid replacing core infrastructure .
Pricing and Cost Structure
Saris AI does not publish transparent pricing on its website. The platform operates on an enterprise sales model targeting financial institutions .
This pricing approach is standard for enterprise software serving regulated industries. Banks and credit unions typically negotiate contracts based on deployment scope, number of workflows, and institution size.
The absence of public pricing makes it difficult for smaller institutions to assess fit without engaging sales. Potential customers should request detailed proposals including implementation timelines, per-workflow costs, and any usage-based components.
For context on value, 8VC reports that at a trillion-dollar institution, Saris demonstrated roughly $28 million in combined annual ROI across just three teams . This figure comes from an investor and has not been independently verified.
Security and Compliance
Saris AI holds SOC 2 Type II certification, according to third-party databases . SOC 2 Type II is an auditing standard that evaluates a service organization’s controls related to security, availability, processing integrity, confidentiality, and privacy.
The company is also listed as GDPR compliant . However, the platform does not hold HIPAA or ISO 27001 certifications according to available records .
Important distinction: SOC 2 Type II certification confirms that an independent auditor evaluated the company’s security controls over a period. It does not automatically mean the company implements Zero Data Retention policies. Data retention practices are separate from SOC 2 compliance and should be verified directly with the vendor.
Domain security signals include TLSv1.3, HSTS, and DMARC . These are baseline security practices for enterprise software.
For financial institutions evaluating Saris, key questions should include: Where is customer data stored? What are the data retention policies? Does the platform process or store personally identifiable information? What happens to data if the contract ends?
Who Should Use Saris AI?
Saris AI is designed exclusively for financial institutions, specifically banks and credit unions in North America.
Ideal fit:
- Mid-size credit unions seeking to scale lending operations without adding headcount
- Large banks with high-volume back-office processing needs
- Institutions using Fiserv, Encompass, or MeridianLink who want to avoid system replacement
- Organizations with lending teams spending significant time on document collection and compliance checks
Not a fit:
- Individual consumers or small businesses
- Non-financial industries
- Institutions requiring on-premise-only deployment (availability not publicly confirmed)
- Organizations outside North America (no international deployment evidence found)
The company reports that customers are live in approximately 90 days with no dedicated implementation engineering staff, a shorter timeline than typical financial services deployments .
Competitive Landscape
The agentic AI space for financial services is competitive. Several companies target similar problems with different approaches.
Saris differentiates through its vertical focus on banking back offices and its desktop integration approach. The company’s claim that roughly 75% of workflow definitions overlap across institutions suggests its upfront investment in mapping lending processes creates transferable value .
Technical Considerations
Several technical aspects warrant scrutiny for institutions evaluating Saris.
Integration Architecture. Saris builds direct bindings to banking software rather than using screenshot-based automation. This requires deeper integration work upfront but may produce more robust long-term results. The system operates through a native desktop application, which means the user’s machine remains available during workflow execution .
Workflow Complexity. The platform is designed for multi-turn, non-linear workflows. Traditional sequential automation cannot handle processes where downstream discoveries require upstream corrections. Saris addresses this with workflow looping and self-healing agents .
Model Transparency. Saris does not publicly disclose which AI models power its agents. For institutions with model governance requirements, this information would need to be obtained through direct engagement.
Deployment Timeline. Saris reports 90-day deployment timelines without dedicated implementation engineering . This is faster than industry standards for comparable systems, but prospective customers should validate this claim with reference customers.
Data Handling. The platform processes sensitive financial data including loan applications, account histories, and personal information. The specific data retention policies, encryption standards, and audit logging capabilities are not publicly documented.
Latest Developments
Saris AI announced its $28.8 million Series A funding round in May 2026 . The company has raised $36 million total to date .
The funding will support scaling to more financial institutions, strengthening integrations with partners like Fiserv, Encompass, and MeridianLink, and expanding the team that trains and deploys agents .
Saris demoed at FinovateFall 2026, a financial technology conference . The company also participated in FinovateSpring 2026 .
The company’s growth trajectory shows rapid customer acquisition. According to 8VC, sales cycles are short for the segment, with customers signing without pilots . This contrasts with typical financial services software procurement, which often involves lengthy pilot programs.
Frequently Asked Questions
What does Saris AI do?
Saris AI builds agentic workflow automation for banks and credit unions. Its AI agents handle back-office tasks including lending, compliance checks, document processing, and data validation, integrating with existing banking systems.
Who founded Saris AI?
Danial Jameel, Alice Dinu, and James Dang founded Saris AI. The team previously built Oohlala Mobile, a Y Combinator-backed startup that became Ready Education .
How much funding has Saris AI raised?
Saris AI has raised $28.8 million in Series A funding and $36 million total to date. The Series A was led by 8VC with participation from Audacious Ventures, Homebrew, Btech Consortium, and Service Ventures .
Is Saris AI SOC 2 compliant?
Saris AI holds SOC 2 Type II certification according to third-party databases . This certification confirms independent audit of security controls but does not automatically indicate Zero Data Retention policies.
What makes Saris AI different from RPA tools?
Saris AI uses agentic AI that can handle non-linear, multi-turn workflows with self-healing capabilities. Traditional RPA automates clicks and breaks when processes deviate from the expected path .
Conclusion
Saris AI targets a specific and significant problem: the manual, fragmented back-office workflows that consume time and resources at financial institutions. The company’s agentic approach moves beyond simple click automation to handle the complexity of lending and compliance processes.
What matters most is the integration strategy. By building direct bindings to existing banking software rather than requiring system replacement, Saris reduces adoption friction. The reported 90-day deployment timeline, if accurate, represents a meaningful improvement over industry norms.
The platform appears suited for mid-size to large financial institutions in North America that process high volumes of lending and compliance work. Organizations using Fiserv, Encompass, or MeridianLink are natural fits given the stated integration partnerships.
Important limitations exist. Pricing is not public, making budget assessment difficult without engaging sales. The platform does not hold ISO 27001 or HIPAA certifications. Data retention and privacy policies are not publicly documented.
Institutions evaluating Saris should request reference customers, validate deployment timeline claims, and obtain detailed information about data handling practices. The technology appears promising for the right use case, but enterprise buyers should conduct standard due diligence before committing.
