Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
✕
Sequel
✓ verifiedFreemium
Governed data layer connecting marketing, product and finance sources to AI agents for plain-language querying.
6.4K visits/mo4.3K saves
✕
Devin AI by Cognition
✓ verifiedPaid
Autonomous AI software engineer by Cognition that plans and completes full coding tasks from a natural-language brief.
Pricing
No public pricing
DEVELOPER: FREE
STARTER: $119 / month
GROWTH: $599 / month
ENTERPRISE: Starting at $1,800 / month
Free: $0/mo (1 data source, 1 user)
Pro: $19/mo (unlimited data sources, 1 user)
Team: $99/mo (unlimited data sources and users, Slack access)
No public pricing
No public pricing
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Developer-first platform for AI-powered integrations
- ✦Secure, isolated sandboxes for running JavaScript/Python code
- ✦Automatic management of npm/PyPI dependencies
- ✦Built-in platform plumbing: secrets, webhooks, scheduling, logs, and audit
- ✦Yep Agent (prompt → runnable processes)
- ✦MCP Server/Tools (convert code into AI agent tools)
- ✦Serverless runtime (YepCode Run) and SDK access
- ✦Unified connection to 100+ marketing/product/finance data sources
- ✦MCP-compatible interface usable by any AI agent
- ✦Learns custom metric definitions and joins across sources
- ✦Secure credential gateway that keeps raw keys from agents
- ✦Cross-source joins spanning databases, warehouses and product data
- ✦Fine-grained audit logs of every query
- ✦Live dashboards and debugging in plain English
- —
- ✦Autonomous end-to-end task execution
- ✦Planning and multi-step reasoning
- ✦Code writing, running and debugging
- ✦Integrated shell, editor and browser
- ✦Application building and deployment
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Building complex API integrations that require custom code and logic beyond what no-code tools offer.
- →Safely running AI-generated scripts in isolated environments with secrets management.
- →Automating workflows that require large datasets, loops, branching, or custom dependencies.
- →Connecting AI agents to external databases, APIs, and services using MCP tools.
- →Marketing teams asking AI agents for campaign or ROAS reports
- →Data teams governing access to metrics across tools
- →Agencies building AI-driven client reporting
- —
- →Automating software engineering tasks
- →Building apps from a brief
- →Debugging and fixing code
- →Assisting development teams
Visit