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Resolvd AI secures $1.6 million pre-seed funding from Spice Capital, Betaworks, and Factorial Capital.
Funding will be used to expand the engineering team and enhance the company’s core product.
The platform automates complex data reconciliation tasks for IT and operations, aiming to eliminate error-prone, manual data work.
Strong backing includes experienced founders and renowned angel investors like Olivier Pomel (Datadog) and Clement Delaunay (HuggingFace).
Modern enterprises operate with a tangled web of platforms, services, and data pipelines. For teams in IT and operations, reconciling data between these disparate systems isn’t just tedious—it’s a critical, failure-prone bottleneck. Unstructured requests and manual processes often mean hours, sometimes days, lost to tasks that seem simple but are anything but.
Resolvd AI, founded by Ananth Manivannan (former PepsiCo, Capital One), spotted a universal pain point: the need for an intelligent, reliable way to automate complex reconciliation workflows and reduce costly human errors. With its AI-driven platform, Resolvd AI enables teams to reclaim valuable engineering time, focus on innovation, and minimize mistakes in mission-critical operations.
Resolvd AI’s pre-seed round attracted a diverse syndicate of early-stage backers:
Spice Capital, led by Forbes 30 Under 30 investor Maya Bakhai, cited the team’s “mission to change an error-prone, manual necessity into a streamlined, scalable process.”
Betaworks and Factorial Capital, both known for backing ambitious infrastructure and developer tools, saw clear market demand for Resolvd AI’s automation-first approach.
Impressively, the syndicate also includes angel investors with deep cloud and AI experience, strengthening the company’s technical depth as it scales its product and team.
Resolvd AI doesn’t just digitize existing processes—it autonomously handles the messy business of reconciling records across platforms, clouds, and internal services.
The platform’s heart is an AI-powered workflow engine that:
Interprets unstructured requests, whether from IT or business teams.
Maps and cross-references data spread across various internal systems.
Detects errors, inconsistencies, or missing pieces, and flags or resolves them before they become major issues.
Offers teams both real-time insights and an audit trail of actions—crucial for compliance and troubleshooting.
Unlike most platforms, Resolvd AI emphasizes collaborative, transparent automation. This means humans can intervene, review, and refine processes as needed. The artificial intelligence (AI) learns and adapts with every new reconciliation challenge, making it ever-more effective for large and growing organizations.
The $1.6 million investment will be used primarily to:
Scale the core engineering team, attracting specialists with backgrounds in cloud automation, AI, and data infrastructure.
Accelerate product development, rapidly improving features that tackle more complex data scenarios.
Enlarge customer reach—resolvd AI already counts major US healthcare systems among its early adopters.
Most importantly, the fresh capital positions Resolvd AI to cement itself as an indispensable layer for enterprise-scale automation at a moment when organizations are hungry to cut costs, eliminate manual bottlenecks, and prepare for a future where AI is essential in the back office as well as the customer-facing front.
With talent from both engineering and real-world operations, Resolvd AI is poised to set a new bar for AI-powered internal automation. The movement from “automate what you can” to “let AI proactively handle the work only humans could do” is fast becoming a necessity.
Expect more IT teams and operations leaders to explore the advantages of this kind of answer engine for the back office—bringing speed, accuracy, and resilience to daily enterprise workflows.
This news signals not just a milestone for Resolvd AI, but a larger shift for how enterprises think about manual, repetitive work—and who (or what) should really be doing it.

Editorial Team
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