Daloopa raises $47M Series C for AI-driven finance data platform
Serge Bulaev
Daloopa has raised $47 million in a Series C funding round, which may help the company hire more staff and expand its data coverage. The funding suggests Daloopa will continue developing AI-driven finance tools that link each data point to its source. New capital might also allow faster product rollouts and global expansion, though no clear timeline has been given. Analysts believe Daloopa could become an important platform as the finance industry moves toward more unified data and AI solutions.
Daloopa has secured $47 million in a Series C funding round to scale its AI-driven finance data platform, reinforcing its position as essential data infrastructure for the industry. Announced on May 28, 2026, the round was led by Brighton Park Capital with participation from Squarepoint Capital, Touring Capital, and Nexus Venture Partners.
Analysts typically view Series C funding as growth capital, indicating Daloopa is poised to accelerate hiring for its engineering, product, and go-to-market teams. The investment will also deepen data coverage beyond its current company portfolio and advance AI-native product development focused on linking every data point to its source for complete auditability.
Why the round matters for finance leaders
This funding round signals Daloopa's readiness to scale, promising accelerated hiring to improve customer support and faster development of new data connectors. For finance leaders, it underscores the market's shift toward AI-powered tools that offer greater auditability and integration with existing cloud and large language model ecosystems.
- Expanded Talent: Daloopa plans to grow its engineering and sales teams, which is expected to reduce customer onboarding times and improve support.
- Enhanced Data Delivery: With existing integrations for Excel, APIs, and cloud platforms like Snowflake and Databricks, the new capital will likely accelerate the rollout of additional data connectors.
- Advanced AI Capabilities: Daloopa positions itself as the foundational data layer for agentic workflows, suggesting the funding will strengthen its Large Language Model (LLM) tools, building on its recent MCP integration with Anthropic's Claude.
Benchmarks for an internal pilot
Finance leaders evaluating the platform's return on investment (ROI) can implement a controlled 90-day pilot using the following framework:
- Scope: Dedicate the pilot to one financial modeling team and two related FP&A processes.
- Metrics: Track key performance indicators such as model update time, error rates, and the frequency of manual source verification.
- Target Lift: Daloopa's benchmark claims report up to a 70% reduction in time for new model builds and about 2 hours saved per ticker during earnings updates; they are presented as benchmark results, not a target lift.
- Data Assurance: Confirm that all data points within Excel exports maintain a direct link to their original source, ensuring full auditability.
Building the business case
When presenting the business case to leadership, finance and procurement teams can frame the platform's benefits around three primary cost-saving areas.
| Cost driver | Baseline pain point | Potential impact |
|---|---|---|
| Analyst hours | Earnings-season model refreshes average 30-60 minutes each | Time savings may free 8-12 hours per analyst quarterly |
| Data purchase | Multiple subscriptions for transcripts and filings | Consolidation could lower duplicate spend |
| Error remediation | Manual cross-checks of figures | Source-linked fields reduce rework risk |
Vendor checklist highlights
Before finalizing a contract, due diligence should include confirming the following technical and security requirements:
- Confirm a clear integration path for cloud data warehouses like Snowflake or storage solutions like AWS S3.
- Ensure the selected license tier provides API rate limits sufficient for projected peak usage.
- Validate security and compliance by reviewing the platform's SOC 2 report and data provenance controls.
According to the official press release, the proceeds will also fuel global expansion, potentially establishing regional support desks for 24-hour trading cycles. While no specific product timeline has been released, this new capital positions Daloopa to compete effectively in a market rapidly moving toward unified data, AI, and workflow automation platforms.
What did Daloopa announce on May 28, 2026?
On May 28, 2026, Daloopa announced a $47 million Series C led by Brighton Park Capital with participation from Squarepoint Capital, Touring Capital, and Nexus Venture Partners. The capital will be used to expand hiring across engineering, product, and go-to-market, deepen global data coverage, and scale AI-native products for financial services workflows.
How will the funds accelerate Daloopa's product roadmap?
Daloopa plans to triple down on AI-driven data infrastructure, releasing three clear deliverables for CFOs and finance teams:
- Pilot plan - a 30-day guided rollout to benchmark ROI against existing research workflows.
- Business-case template - pre-built Excel and API scenarios quantifying potential time savings per model and reduction in ramp time.
- Vendor checklist - security, auditability, and data-coverage criteria that align with current finance-automation trends.
What specific capabilities does the platform offer today?
- Extensive public company coverage globally with 14 years of history and significantly more data points than legacy providers.
- Source-linked cells in Excel and API outputs, enabling full auditability and traceability.
- Multi-channel delivery: Excel add-in, REST API, Snowflake, Databricks, and AWS S3.
- MCP-ready (Model Context Protocol) integrations for LLMs like Claude and OpenAI, powering agentic automation workflows.
Which finance roles gain the most immediate value?
- FP&A teams cut quarterly model-update cycles during earnings season.
- Procurement & vendor management validate supplier financials faster with structured, sourced data.
- Investment banking & PE analysts run valuation and comps workflows that auto-refresh when new filings hit EDGAR.
- Chief Data Officers plug high-granularity datasets into internal AI pipelines without manual cleaning.
What market trends make this Series C especially timely?
According to industry reports, a significant portion of finance functions are expected to deploy AI-enabled technologies, while many will run internal AI platforms. The shift toward unified CPM suites and real-time forecasting pressures CFOs to consolidate fragmented tools. By injecting $47 million into AI-native data infrastructure, Daloopa is positioning itself as the data layer that unifies planning, reporting, and agentic decision support in one environment.