Best AI Development Platforms for Amazon API Gateway

Zerve is the agentic data workspace designed for anyone who works with data, from solo analysts, data scientists and business users alike. Zerve brings together exploration, advanced analysis, collaboration, and production deployment into a single AI-native environment, so that important data work doesn’t stall, break, or disappear. Zerve is used by data professionals in companies such as BBC, QVC, Dun & Bradstreet, Airbus, and many others. Zerve makes advanced data work accessible, durable, and deployable from day one, starting with the messy, real-world data most projects begin with. At the heart of Zerve is a new way for humans and AI agents to work together. Zerve’s AI agents understand the full context of a project and actively help plan, build, debug, and iterate across multi-step analyses. Agents can assist with tasks like cleaning and transforming data, identifying issues, and testing approaches, reducing the manual effort that slows teams down. This means working at a higher level of abstraction without being slowed by setup or syntax. With Zerve, you always have an expert data scientist at your side, guiding decisions, suggesting next steps, and taking action. Unlike traditional data notebooks, workflows in Zerve are reproducible and stable. Users can work across Python, SQL, and R in a single workspace, connect directly to databases, data lakes, and warehouses, and integrate with Git for version control. The built-in distributed computing engine powers massively parallel execution for large-scale analysis, simulations, and AI workloads, with multi-agent orchestration coordinating complex pipelines behind the scenes. Zerve can be used as SaaS, self-hosted, or even on-premise for regulated environments.

MCPTotal is a robust, enterprise-level solution that facilitates the management, hosting, and governance of MCP (Model Context Protocol) servers and AI-tool integrations within a secure, audit-friendly framework, rather than allowing them to operate haphazardly on developers' local machines. The platform features a “Hub,” which serves as a centralized, sandboxed runtime space where MCP servers are securely containerized, fortified, and thoroughly vetted for potential vulnerabilities. Additionally, it includes an integrated “MCP Gateway” that functions as an AI-focused firewall, capable of real-time inspection of MCP traffic, enforcing security policies, tracking all tool interactions and data movements, and mitigating typical threats like data breaches, prompt-injection attempts, and improper credential use. Security measures are further enhanced through the secure storage of all API keys, environment variables, and credentials in an encrypted vault, effectively preventing credential sprawl and the risks associated with storing sensitive information in plaintext on personal devices. Furthermore, MCPTotal empowers organizations with discovery and governance capabilities, allowing security teams to conduct scans on both desktop and cloud environments to identify the active use of MCP servers, thus ensuring comprehensive oversight and control. Overall, this platform represents a significant advancement in the management of AI resources, promoting both security and efficiency within enterprises.