Agentic AI banking platform Saris closes $28.8M Series A to automate 70% of lending workflows

With a round led by 8VC, the San Francisco startup is targeting the back-office bottleneck that costs financial institutions billions in redundant manual labour, and it already has results to show.

Saris, a San Francisco-based agentic workflow platform built for banks and credit unions, raised $28.8 million in Series A financing on 28 May 2026. The round was led by 8VC, the Austin-based venture firm with over $6 billion in assets under management, with co-investment from Audacious Ventures, Homebrew, Btech Consortium, and Service Ventures. The capital will fund platform expansion across additional financial institutions, deeper integration with core banking vendors Fiserv, Encompass, and MeridianLink, and headcount growth across the agent training and deployment team.

What problem is Saris actually solving?

The short answer: the back office of most financial institutions has not kept pace with front-end digital transformation. Lending, compliance, and operations teams at community banks and credit unions still spend significant portions of each day on manual document review, data entry, and validation tasks, work that carries low cognitive load but high labour cost. McKinsey's 2026 Global Banking Annual Review noted that fintechs have now claimed 17% of industry revenues and are accelerating, creating structural competitive pressure on institutions still running paper-heavy processes.

Saris deploys AI agents that are trained on a given institution's existing workflows and then execute those workflows autonomously, under human oversight. The platform integrates with the core banking systems already in place rather than replacing them, a design choice that lowers adoption friction and avoids the costly rip-and-replace cycles that have slowed AI rollout elsewhere in financial services.

How does the platform perform in practice?

According to Saris, institutions using the platform have automated up to 70% of consumer, mortgage, and commercial lending tasks, reduced operational costs by up to 35%, and more than doubled output without adding headcount. Those figures come from the company's own reporting, and independent verification is pending as the platform scales. Still, the early client testimonials indicate measurable ROI rather than proof-of-concept outcomes.

"We needed an AI strategy with a clear ROI, something that can help us compete and grow using existing resources. Saris provided a single, end-to-end solution that streamlines workflows and integrates with our existing technology for easy adoption."

Matt Mayo, CRO, Community Bank

Diana Hennel, CTO and SVP at Catalyst Corporate Credit Union, added that the platform reduced manually intensive processes while improving accuracy and retaining human oversight, two requirements that regulators and compliance officers consistently flag when evaluating AI deployments in financial services.

Why is 8VC betting on community banking AI now?

8VC founding partner Alex Kolicich framed the investment thesis around a market gap rather than a technology trend: financial institutions of every size have been underserved by technology that was not built for the complexity of modern banking operations. That observation aligns with broader data. Global banking technology spending reached $650 billion in 2023, yet productivity at US banks has declined by 0.3% annually since 2010, a divergence that points to misallocation rather than underinvestment. The agentic AI market in financial services, currently valued at approximately $2.1 billion, is projected to reach $80.9 billion by 2034 at a compound annual growth rate of 43.8%, according to market research cited by EINPresswire.

The timing also reflects a maturation in enterprise AI adoption. KPMG research based on more than 17 million firms estimates that agentic AI will contribute $3 trillion in corporate productivity, with organisations achieving an average 2.3x return on investment within 13 months of deployment. The window for first-mover advantage in community bank automation is narrowing, and Saris is positioned early.

What does the competitive landscape look like?

Saris enters a market that is drawing serious capital. A wave of startups is pitching agentic AI to financial institutions, but most target the largest banks, where budgets are larger and procurement cycles are longer. Saris differentiates on the community bank and credit union segment, institutions that collectively hold trillions in assets but have historically been the last to receive enterprise-grade technology. The integrations with Fiserv, Encompass, and MeridianLink are strategically significant: these three vendors together serve a substantial portion of community financial institutions in the United States, meaning Saris can ride existing distribution rather than building its own.

"Our vision is a future where humans and AI work side by side in financial services. The best institutions won't replace people; they'll give people the leverage to do more with less strain."

Danial Jameel, co-founder and CEO, Saris

What will the $28.8M fund?

The Series A capital has three stated uses. First, scaling the platform to a broader set of financial institutions, with community banks and credit unions the primary targets. Second, deepening the technical integrations with Fiserv, Encompass, and MeridianLink to reduce deployment time per institution. Third, expanding the team responsible for training and deploying Saris agents on a per-institution basis, a labour-intensive process that the company treats as core to its differentiation, since agents trained on institution-specific workflows outperform generic models on compliance-sensitive tasks.

CEO Danial Jameel has indicated the immediate focus is on bringing measurable results to more institutions faster, rather than expanding into adjacent verticals. That suggests the next 12 to 18 months will be about deepening penetration in financial services rather than horizontal expansion.

Why this matters to FinanceX readers

For finance professionals and investors, the Saris raise is a data point in a broader shift: the AI productivity dividend in banking is beginning to accrue not just to tier-one institutions but to the long tail of community banks and credit unions. Institutions that automate lending workflows at scale stand to compress cost-to-income ratios materially, a metric that directly affects equity valuations. Investors watching the fintech funding cycle should note that the 8VC-led round signals institutional conviction in purpose-built, integration-first AI platforms over general-purpose models, a distinction that is increasingly influencing enterprise procurement decisions. The implied bet is that the winning AI vendors in banking will be those who train on institution-specific data and integrate with incumbent core systems, not those who ask institutions to migrate.