AI-powered financial planning platform with Excel-native interface
Solver builds a cloud xFP&A platform designed to democratize financial planning beyond finance teams. The stack reveals a hybrid approach: C# / ASP.NET backend on Azure + Snowflake for analytics, paired with native Excel integration and now AI workflows (GPT). Active projects signal a shift toward verticalized, pre-built solutions—standardized integrations and proof-of-concept dashboards for specific industries—while data quality and scalable deployment challenges suggest the platform is maturing from single-customer implementations toward product-driven growth.
Solver provides a cloud-based extended financial planning and analysis (xFP&A) platform for mid-market finance and operations teams. The product combines Excel-native interfaces with AI-powered workflows, templates, and a data warehouse (Snowflake) to enable planning, reporting, consolidation, and forecasting across organizations. The company operates with 51–200 employees based in Calabasas, CA, and has built a partner ecosystem providing local and industry-specific expertise. Core differentiation centers on rapid implementation via pre-built templates and integration technology, allowing users to move from data source to actionable dashboard in weeks rather than months.
Solver's backend runs on C# / ASP.NET Web API with SQL Server and Azure; analytics layer uses Snowflake and Azure Synapse. Front-end leverages Excel-native components. AI capabilities integrate GPT. Sales and operations run on Salesforce, HubSpot, and Asana.
Current project focus includes AI-powered product features and GPT-based workflows, standardized integration layers for vertical solutions, financial reporting and dashboard development, and scalable data model creation. Active work on data quality optimization and proof-of-concept dashboards for pre-sales.
Solver's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.