Mammoth in 2026: From Data Tools to an AI-Native Data Operating System
In 2025, Mammoth didn’t just add AI features.We removed configuration, manual handoffs, and the assumption that data work requires specialists. Over the course of the year, Mammoth shipped 52 weekly releases, launched 15+ AI-native capabilities, and delivered 200+ platform enhancements. Customers now process billions of rows monthly, achieving 300–1000% ROI, while business users operate independently—often
In 2025, Mammoth didn’t just add AI features.
We removed configuration, manual handoffs, and the assumption that data work requires specialists.
Over the course of the year, Mammoth shipped 52 weekly releases, launched 15+ AI-native capabilities, and delivered 200+ platform enhancements. Customers now process billions of rows monthly, achieving 300–1000% ROI, while business users operate independently, often within their first week.
What emerged is something fundamentally different from a traditional data platform: an AI-first data operating system where intent replaces configuration, and workflows run autonomously.
Mammoth Became AI-First
What used to require a data engineer now starts with a sentence.
Across the platform, natural language replaced technical configuration. Users describe what they want in plain English, and Mammoth generates the technical implementation automatically.
Key Capabilities:
- Intent-Based Transformations
Pipeline creation from 20+ minutes to 30 seconds.
Example: “Find duplicate orders and keep the most recent” generates complete pipeline automatically. - Generative AI
Enrich, transform, and generate datasets across 50K rows using simple prompts.
Use cases include synthetic data creation, missing value derivation, and calculated field generation. - Natural Language Everywhere
Filters, conditions, text extraction, and SQL queries all accept plain English input, with AI generating the technical logic behind the scenes.
Impact
- 60% faster workflows than manual configuration
- 90% of users achieve independence within first week
- 70% reduction in support tickets.
Below: Preview of SQL Query – Type in your intent to generate a SQL query to transform your data
Enterprise Automation Matured
Manual data operations gave way to governed, zero-touch workflows.
Mammoth evolved from task-based automation to a full enterprise orchestration platform, enabling regulated, auditable, and scalable automation.
Key Capabilities:
-
Orchestration Platform
- Dataset Refresh (automated third-party data pulls)
- Data Consolidation (multi-file combining with validation)
- Messaging (conditional alerts with data attachments)
-
Activity Log
Complete workspace audit trail for regulatory compliance. Every transformation and data access fully traceable. -
Subscription Management
Self-service workspace administration with billing automation, user/project governance, alpha/beta feature controls.
Impact
Customers automated workflows that previously required daily manual intervention, reducing operational reporting cycles and enabling zero-touch data operations.
Below: Preview of Activity Log and Orchestration Features
Data Intelligence Was Democratized
Data quality and insight discovery moved upstream, before errors reached production.
Business users gained independent access to data quality assessment and AI-powered insights, without technical training.
Key Capabilities:
- Data Quality Scoring
DAMA framework-based profiling with completeness scoring, critical issue identification, and actionable recommendations. - Insights Panel
Automatic identification of patterns, anomalies, and potential risks. - Public Processing
PDF and image extraction without account creation – ideal for consultants and one-time workflows.
Impact:
- 95% reduction in production data errors
- Quality issues identified before downstream systems
- Business users assess and validate data independently
Below: Preview of Data Quality Scoring
NEW: AI-Powered Dashboards (Beta)
Dashboards stopped being projects. They became conversations.
In 2025, Mammoth launched conversational dashboard creation in controlled beta. Business users now build executive-ready dashboards in minutes using natural language.
Key Capabilities:
- 17+ Widget Types
KPIs, trend charts, funnels, treemaps, Sankey diagrams, radar charts, and more - Smart Auto-Layout
AI-driven placement using a responsive 12-column grid with 10 professional themes - Three Sharing Modes
Public (no login), Password-Protected, Authenticated access
Early Beta Results
- Dashboard creation time reduced from days to ~15 minutes
- Potential to eliminate $75K+ annually in external BI licensing for board reporting
Below: Preview of AI Powered Dashboard
2025 Releases: A Compressed Timeline
January
- Enhanced join functionality with CSV download for non-unique values
- Platform stability improvements across pipeline execution
- PDF to CSV Public App: Free public tool for converting tables in PDFs to CSV — try it, no account needed. No account required.
February
- Automation (Alpha): First automated file upload workflows
- Dataset schema editing capabilities
- Intent-based text extraction
Impact:
Intent-based text extraction let users type natural language requests like “find all email addresses” instead of writing regex patterns. Early alpha feedback informed our broader AI development.
Below: Preview of Intent-based text extraction
Early Adopter Feedback:
“I’ve been avoiding regex for years. This is incredible.”. Financial Services Customer
March
- Password-protected ZIP file support
- Data quality improvements across explore cards
- Batch processing enhancements
- AI development continued in alpha
April
- Intent-based transformations (Beta): Natural language for data transformations
- Intent-based condition builder
- Enhanced workspace and project management
- Paste task improvements for faster workflow building
Metrics: Pipeline creation 20+ minutes → 30 seconds. 60% faster than manual configuration.
Below: Preview of intent-based Transformation
May
- Generative AI: AI-powered data enrichment and transformation
- SQL Query AI: Natural language to SQL generation
- AI-assisted connector query generation
- SAP & HANA connector support
Impact:
Users could generate synthetic datasets, enrich data with calculated fields, and transform 50K rows with simple prompts. Production customers began using this for multi-country product standardization at 1B+ rows monthly scale.
Below: Preview of Generative AI
Customer Quote:
“Our business analysts built pipelines in 15 minutes that would have taken our data engineers hours. The learning curve essentially disappeared.”. CPG Customer
June
- Intent-based condition builder (production)
- AI-powered text extraction (production)
- External API key management
- Enhanced data quality with whitespace highlighting
Impact:
Natural language interfaces deployed across the platform for conditions, filters, text extraction, and transformations. A Financial Services customer achieved 1000% ROI improvement, their 30-hour monthly process dropped to 4 hours.
Below: Preview of intent-based Condition Builder
July
- NetSuite connector: Enterprise ERP integration
- BigQuery publishing (managed export)
- Alpha/Beta feature toggle for workspace owners
- Enhanced orchestration capabilities
Impact:
Seamless and frictionless integration with PowerBI and Tableau saving money and time
August
- Freeze column functionality for large datasets
- Multi-select behavior improvements
- Enhanced bulk operations
- Global search improvements
- Performance optimizations for 200+ dataset folders
Impact:
Platform handling enterprise scale without degradation
September
- Activity Log (Initial Release): Complete workspace audit trail
- Data Profiling (Alpha): DAMA framework quality scoring
- Enhanced user management with bulk invite
- Preserve join configuration for schema consistency
Impact:
MUFG Bank implemented Activity Log for regulatory compliance with complete audit trail across 19-country KYC automation. First alpha customers using DAMA framework scoring, automated quality assessment replacing manual data audits.
Below: Preview of Activity Log
Customer Impact:
“The Activity Log gives us the regulatory audit trail we needed. Every transformation, every data access, every user action, completely traceable.”. Compliance Director, Financial Services
October
- PDF to CSV (Production): AI-powered table extraction
- Image to CSV: Extract structured data from images
- Enhanced data quality modal
- Workspace deletion with subscription cancellation
- SQL Union query support
Impact:
10x faster than manual data entry with 95%+ accuracy on structured documents. 30% of active customers adopted PDF/image extraction within first month. Key use cases: financial statements, invoice processing, regulatory documents, historical data digitization.
Below: Preview of intent-based PDF extraction
Performance:
10x faster than manual data entry. 95%+ accuracy on structured documents.
Use Cases Unlocked:
- Financial statements from PDF to analysis-ready data
- Invoice processing at scale
- Regulatory document extraction
- Historical data digitization
Customer Adoption:
30% of active customers using PDF/image extraction within first month. This became a key differentiator in sales conversations.
November
- AI-Powered Dashboards (Beta): Conversational dashboard creation
- Orchestration Platform (Production): Complete workflow automation
- Bulk replace enhancements
- Pipeline attribution (show who created/modified)
Impact:
Dashboards: 17+ professional widget types, 10 designed themes, smart auto-layout, three sharing modes (public, password, authenticated). Early beta users creating board presentations in 15 minutes versus 4-6 hours of PowerPoint preparation.
Orchestration: Complete workflow automation with Dataset Refresh (automated third-party data pulls), Data Consolidation (multi-file combining), and Messaging (conditional alerts). Hospitality customer automated 70+ property daily reporting with zero manual intervention.
Below: Preview of Insights Panel
December
- Dashboard performance optimizations: Billion-row dataset support
- Insights Panel (Production): AI-powered data observations
- Project-level settings: Centralized date format management
- Intent-based display properties: Context-aware UI
- Generate dataset using AI: Create sample data from prompts
- Enhanced UI/UX across platform
Impact:
95%+ customer retention, 65-70% enterprise sales win rates, 90% self-service capability for business users, 70% reduction in support tickets year-over-year.
Starbucks harmonised sales data from 17 countries, processing 1B+ rows monthly. The monthly reporting cycle dropped from 20 days to hours.
What’s Next: 2026 Roadmap
Q1: Dashboard General Availability
Performance optimization for billion-row datasets, advanced customization, PDF export, scheduled delivery, mobile app integration, enterprise sharing controls.
Q2: Enhanced Orchestration
File Collection (8 cloud storage sources), PDF Orchestration, event-based triggers, Slack/Teams integration, advanced cron scheduling.
Q3: Collaboration & Governance
Real-time collaborative editing, version control with branching, enhanced RBAC, data lineage visualization, impact analysis.
H2: AI Agent Evolution
Multi-step autonomous workflows, predictive quality recommendations, intelligent schema mapping, natural language business logic, self-healing pipelines.
