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Enterprise-grade open-source technologies trusted by thousands of companies worldwide.
A visual data pipeline platform powered by AI agents — build, deploy, and manage complex data workflows with drag-and-drop simplicity. From ideation to production in minutes.
By the Numbers
Pipelines Deployed
Uptime SLA
Integrations
Rows/Sec Processed
Stop juggling multiple tools. One unified platform for all your data pipeline needs.
Describe your pipeline in plain English. AI creates production-ready flows with auto-fix suggestions and performance optimization.
Apache Spark-powered with 20+ transformation nodes. Connect to PostgreSQL, MySQL, Snowflake, BigQuery and more.
REST APIs, webhooks, OAuth, JWT authentication. Apache Camel for robust enterprise microservices.
CSV, JSON, XML, Excel, Parquet. Smart engine selection for optimal performance across formats.
Apache Kafka integration with sub-millisecond latency for live data streams and event processing.
Train, score, and manage ML models directly within your pipelines. PySpark ML and custom models built in.
AI agents that plug into your entire data stack — databases via JDBC, streaming through Kafka, extensibility via MCP. Run PySpark jobs, execute SQL queries, schedule pipelines, and orchestrate workflows — all from a single prompt.
LLM-driven tool-calling loop with database, SSH, MCP, and code generation tools. The agent takes real action — not just suggestions.
Connect any LLM provider — OpenAI, Claude, Gemini, Ollama, Groq, and more. Each user configures their own API keys and model preferences.
Native MCP client for infinite extensibility. Connect any MCP-compatible server — the agent uses its tools seamlessly alongside built-in ones.
Production-grade PySpark runtime with auto-dependency installation, credential isolation, and real-time log streaming via WebSocket.
Multi-database operations spanning PostgreSQL, MySQL, SQLite, DuckDB, Redshift, MSSQL, Snowflake, BigQuery, Databricks, ClickHouse, and MongoDB — read, transform, and write across systems in one pipeline.
AGENT / CODEGEN / SMART classification routes each request to the optimal execution path — no wasted tokens, no unnecessary tool calls.
The Thinking Prompt agent is backed by ThinkingMemory — a layered memory architecture that gives it persistent context across sessions. No repeated explanations, no cold starts. The agent remembers your data stack, past designs, and learns from every interaction.
Short-term, Context-aware
Holds your current session context — the active pipeline design, connected databases, in-progress queries, and ongoing conversation state. Cleared when the task completes.
Event-based, Temporal
Recalls past interactions — previous pipeline builds, debugging sessions, optimization decisions, and how issues were resolved. The agent learns from your history.
Knowledge, Concepts
Stores your data knowledge — schemas, table relationships, column naming conventions, team preferences, and domain-specific context. The agent knows your stack.
Skills, Procedures
Retains learned patterns — ETL templates, pipeline recipes, orchestration workflows, and best practices from your org. The agent gets better at building what your team builds.
We built our own programming language for data engineering. ThinkingLanguage combines Apache DataFusion with a clean, expressive syntax — letting you query databases, transform files, orchestrate AI agents, connect to the entire MCP ecosystem, and deploy pipelines in seconds, not hours.
Connect to PostgreSQL, MySQL, SQLite, DuckDB, Redshift, MSSQL, Snowflake, BigQuery, Databricks, ClickHouse, MongoDB, Redis and more using named connections. Write postgres("src", "employees") and credentials resolve automatically from your Connection Bridge.
Process billions of rows in-memory with columnar Arrow execution. Filter, aggregate, join, and transform massive datasets with familiar SQL-like operations and functional pipes.
Call LLMs inline with ai_complete(). Build AI-powered data pipelines that classify, extract, summarize, or generate — all within the same script that queries your data.
Full Model Context Protocol support — both client and server. Connect to any MCP server with mcp_connect(), or expose TL functions to Claude Desktop, Cursor, and Windsurf with mcp_serve(). Agents auto-discover MCP tools alongside native ones — one unified tool list, dispatched transparently.
Read and write CSV, Parquet, and JSON directly. Transfer files securely via built-in SFTP/SCP connectors. Cloud files are automatically resolved and downloaded — work with read_csv("sales.csv") as if every file is local.
Real-time WebSocket-streamed output — see results as they happen, cancel mid-flight. Go from prototype to production with tl deploy. Docker, Kubernetes, and interactive REPL built in.
All your platform connections — databases, APIs, MCP servers, AI providers — are automatically available to every ThinkingLanguage script. No hardcoded credentials, no config files. Just write your logic and the platform handles the rest.
An autonomous AI agent that lives inside your data platform. It doesn't just answer questions — it remembers context, takes action, and watches your infrastructure around the clock. Memory powered by ThinkingMemory.
ThinkingMemory
Learns & remembers schemas, query patterns, team preferences
Plans & executes queries, commands, and integrations
24/7 watch
Pipeline failures, connection health, schema drift
Powered by ThinkingMemory
Persists knowledge across sessions — schemas, query patterns, team preferences. The agent gets smarter over time, powered by the ThinkingMemory architecture.
Autonomous Actions
Runs SQL queries, connects via SSH, calls external APIs, and integrates with MCP servers — autonomously.
Multi-step Reasoning
Multi-step reasoning with automatic tool selection. Describe what you need; the agent figures out how.
24/7 Monitoring
24/7 background monitoring — pipeline failures, connection health, schema drift — detected before you notice.
Event-driven Routing
Routes alerts to Slack, Discord, Teams, Email, PagerDuty, Google Chat, or any webhook — filtered by event type and severity.
You connect your databases and pipelines. ThinkingClaw learns your environment using ThinkingMemory, monitors it continuously, and alerts you the moment something needs attention — through whatever channel you prefer.
From design to deployment, AI agents assist at every stage of your data pipeline lifecycle.
Natural language to pipeline — just describe what you need
Instant error analysis with context-aware fix suggestions
Continuous quality scoring catches issues before deploy
Detects bottlenecks and anti-patterns, suggests fixes
| Feature | varCHAR | Traditional |
|---|---|---|
| AI-Powered Pipeline Generation Describe pipelines in plain English — AI builds, validates, and deploys them automatically. | ✓ Built-in | ✗ None |
| Visual Drag-and-Drop Full visual canvas with drag-and-drop nodes — no code unless you want it. | ✓ Full Canvas | Code Only |
| Unified Platform ETL, streaming, orchestration, monitoring, and AI — all in one place. No tool sprawl. | ✓ All-in-One | Multiple Tools |
| Real-time Collaboration Multiple team members can edit, review, and deploy pipelines simultaneously. | ✓ Live | ✗ None |
| Time to First Pipeline Go from zero to a production pipeline in 30 minutes — not weeks of config and DevOps. | 30 min | 2-3 weeks |
| Cost per Pipeline 85% lower cost than enterprise alternatives — no per-connector or per-row pricing traps. | 85% Lower | Higher TCO |
Enterprise-grade encryption and access controls across every layer of our platform.
Industry-leading encryption standards
Multi-layer authentication security
Comprehensive attack prevention
Secure session management
All critical headers properly configured
Integrated security dashboard for monitoring security events
Professional-grade security patterns
GDPR, SOC 2, NIST standards
We're a DPIIT - Startup India Certified Startup
SOC 2 Type II certification in progress
From idea to production in under 30 minutes. Minimal code required.
Follow us on LinkedInLightning Fast
100x faster pipelines
Zero Learning Curve
Master in minutes
Production Ready
Enterprise infrastructure
varCHAR costs 85% less than big players. Get enterprise-grade data pipelines without the enterprise price tag. No per-row pricing, no per-connector fees, no hidden infrastructure costs. varCHAR's unified architecture eliminates the tool sprawl that drives up traditional platform costs.
vs. enterprise solutions
Build pipelines in minutes
Same budget as 1 Databricks pipeline
Start free, scale as you grow. No hidden fees, no surprises.
Pricing shown is for Developer Edition. Enterprise plans vary based on requirements.
New users get a 21-day Pro trial free!
Contact us for pricing information and custom enterprise solutions.
Choose the deployment option that fits your business needs
Our Developer Edition is cloud-based and ready to use. Get started in minutes with no infrastructure setup.
Custom tailored solutions for enterprises with specific security, compliance, and deployment requirements.
Enterprise pricing may vary according to requirements and package
Join the future of data pipeline development. Start building in minutes, not weeks.
Start building pipelines in minutes, not weeks.
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