Vendors > Datarails

Datarails: AI-Powered, Excel-Native FinanceOS for the Mid-Market

An AI-powered, Excel-native FP&A and finance operations platform designed for mid-market and SMB finance teams that want automation, consolidation, and real-time insight without abandoning spreadsheets.

Vendor Profile

≈ 25 minute read

Updated January 2026

Datarails is an AI-powered, Excel-native FP&A and finance operations platform designed for mid-market and SMB finance teams that want automation, consolidation, and real-time insight without abandoning spreadsheets.

At its core, Datarails treats Excel as the front end and positions its cloud platform as the data engine, workflow engine, and AI layer behind it. The result is a governed, auditable finance system that eliminates manual consolidation, version chaos, and brittle spreadsheet workflows while preserving how finance teams actually work.

Over the past two years, Datarails has expanded from a pure FP&A tool into a broader FinanceOS, covering FP&A, cash management, month-end close, spend control, consolidation, and executive reporting.

1. Snapshot

What Datarails is

An Excel-native finance platform that centralizes data, automates FP&A and close workflows, and layers AI on top of governed financial models.
Positioned as a FinanceOS for mid-market CFOs, not just a planning tool.
Built to scale Excel, not replace it.

Company facts

Founded: 2015
HQ: NYC corporate office with development in Israel
Funding: ~$175M total, including a $70M Series C in January 2026
Employees: 400+
Customers: 1,500+ across industries
Target segment: SMB and mid-market companies

Market momentum

~70 percent year-over-year revenue growth in 2025
Heavy R&D investment in AI and workflow automation
Expanding product surface from FP&A into close and finance operations

2. Who Datarails Is Really For (ICP)

Best-fit customers

Datarails is ideal for organizations that:

Live in Excel and are not willing to give it up
Have outgrown manual spreadsheet consolidation
Need multi-entity, multi-currency reporting
Want automation and governance without heavy IT involvement
Need both FP&A and month-end close support in one platform
Want AI assistance embedded directly in finance workflows

Typical sweet spot:

5 to 500 employees in finance
Mid-market companies with growing complexity
Multi-entity structures
Tech, services, healthcare, manufacturing, consumer, and PE-backed businesses

Less ideal for

Very large enterprises with extreme modeling complexity
Organizations that want to fully abandon spreadsheets
Teams seeking a lightweight budgeting tool only
Companies requiring highly custom modeling languages like Anaplan or Pigment

3. Product Overview and Key Use Cases

Datarails spans the full finance lifecycle, from data ingestion through executive communication.

Core use cases

FP&A and planning

Budgeting and forecasting
Actuals vs budget and forecast analysis
Scenario modeling
Headcount planning

Month-end close

Task coordination and workflows
Reconciliations with sign-offs
Supporting document management
Close visibility dashboards

Consolidation and reporting

Multi-entity consolidation
Currency translation and CTA
Intercompany eliminations
Board-ready financial reporting

Executive storytelling

Dashboards and metrics
Storyboards for board and management decks
AI-generated narrative with live drill-down

What this feels like to a buyer:

Excel stays familiar, but the chaos disappears. Finance moves faster, closes earlier, and spends more time explaining the business instead of reconciling spreadsheets.

4. Architecture and Tech Stack (Under the Hood)

Core philosophy

Excel as the UI, Datarails as the operating system.

Excel files are not databases. Datarails centralizes all data in the cloud and turns spreadsheets into governed views on top of that data.

Key components

Data pipeline and integration layer

200+ connectors across ERP, CRM, HRIS, billing, banks, and data warehouses
API-based ingestion plus secure file uploads
Scheduled or near-real-time refreshes
Automated schema detection

Finance semantic layer

Chart of accounts
Departments and cost centers
Headcount objects
Time and currency rules

Centralized data store

Historical snapshots
Multi-scenario storage
Versioning and audit trails
Single source of truth

Excel add-in (bi-directional)

Pull governed data into Excel ranges
Push modeled outputs back to Datarails
Track formula dependencies and lineage
Lock sensitive cells
Support multi-user collaboration without overwrites

Excel becomes a thin client to a cloud finance platform.

5. AI Capabilities (Genius by Datarails)

Datarails is explicitly AI-native. AI is not an add-on. It is core to the roadmap.

Key AI capabilities

Narrative generation

Automated variance explanations
Board-ready commentary
Monthly business review narratives

Predictive forecasting

Time-series forecasting
Driver inference
Scenario generation

AI agents (2026 expansion)

Auto-mapping new accounts
Auto-detecting anomalies
Auto-generating report templates
Assisting with budget builds

Model intelligence

Explain formulas
Trace drivers
Identify what changed between versions

The long-term vision is a self-maintaining FP&A system that reduces manual finance work by up to 90 percent.

6. Storyboards: Executive Reporting Without PowerPoint

What it does

One-click generation of board-style decks from dashboards
AI-generated commentary focused on material variances
Fully editable narratives
Live drill-down during presentations
Share via link or export to PDF

Strategic intent

Datarails is intentionally not trying to export to PowerPoint. The goal is to keep presentations live, governed, and connected to the data source.

This positions Storyboards as:

A replacement for static board decks
A controlled, auditable reporting artifact
A faster way to turn analysis into insight

7. Integrations and Ecosystem

Datarails integrates with:

ERP and accounting

NetSuite
QuickBooks
Sage
SAP
Oracle

CRM

Salesforce
HubSpot

HRIS

Workday
BambooHR
Gusto

Billing and payments

Stripe
Zuora
Chargebee

Banks and cash platforms

Direct bank connections
Cash management platforms

Data warehouses

Snowflake
BigQuery
Redshift

Integration stance: Centralize everything once, then reuse it everywhere.

8. Implementation and Time to Value

Datarails implementations are fast relative to enterprise FP&A tools.

Typical rollout:

Week 1 to 2

Connect systems, ingest data, define mappings

Week 3 to 4

Validate models, dashboards, and reports

Week 4 to 6

Planning workflows, close workflows, AI insights live

Because teams keep Excel models, most implementations avoid long rebuild cycles.

9. Customer Stories and Outcomes

Datarails has strong proof across mid-market customers.

Oxford Road

Reduced close time by ~80 percent
Cut reporting cycles from days to hours
Live in under one month

Origin Investments

Centralized finance reporting
Improved visibility across entities
Scaled FP&A without adding headcount

Common themes:

Faster close
Fewer errors
Less manual consolidation
More time for strategic analysis
Higher confidence in numbers

10. Go-to-Market and Positioning

Core message

"Excel, but enterprise-grade."

GTM focus

Mid-market CFOs
Controllers and FP&A leaders
Finance teams modernizing without heavy IT

Strategic shift

Datarails is no longer positioning as just FP&A. It is explicitly moving toward owning the CFO tech stack.

11. Strengths and Limitations

Strengths

Best-in-class Excel-native experience
Broad FinanceOS scope
Strong AI capabilities
Fast implementation
High customer satisfaction
Scales well for mid-market complexity

Limitations

Excel-centric by design
Not ideal for extreme enterprise modeling needs
Some proprietary syntax to learn
Workflow depth is strong but lighter than enterprise CPM suites
Storyboards lacks PPT export and bulk generation today

12. When Datarails Is a Great Fit vs Alternatives

Datarails is a great fit if you:

Want to keep Excel at the center
Need automation, governance, and AI
Have multi-entity complexity
Want FP&A and close in one platform
Need faster cycles without IT dependency

Consider alternatives if:

You want a fully web-based experience → Abacum
You want Microsoft-only Excel modeling → Vena, Datarails
You want lightweight spreadsheet governance → Cube
You need advanced custom modeling languages → Pigment

13. Demo Questions to Ask Datarails

Excel and architecture

How does Datarails manage cell-level lineage and versioning?
How are formulas tracked across users?

AI

What tasks are fully automated today vs assisted?
How does AI explain variance drivers?

Close

How are preparer and reviewer roles enforced?
How does reconciliation tie to supporting documents?

Reporting

How do Storyboards stay live during meetings?
How is narrative generated and edited?

Commercials

How pricing scales with entities, users, and modules
What a typical 3-year TCO looks like

Need Help Evaluating Datarails?

Our analysts can help you evaluate Datarails against other Excel-native FinanceOS platforms and determine if it's the right fit for your mid-market finance team.

Book a 20-min Consultation