Bright Data
Bright Data holds the title of the leading platform for web data, proxies, and data scraping solutions globally. Various entities, including Fortune 500 companies, educational institutions, and small enterprises, depend on Bright Data's offerings to gather essential public web data efficiently, reliably, and flexibly, enabling them to conduct research, monitor trends, analyze information, and make well-informed decisions.
With a customer base exceeding 20,000 and spanning nearly all sectors, Bright Data's services cater to a diverse range of needs. Its offerings include user-friendly, no-code data solutions for business owners, as well as a sophisticated proxy and scraping framework tailored for developers and IT specialists.
What sets Bright Data apart is its ability to deliver a cost-effective method for rapid and stable public web data collection at scale, seamlessly converting unstructured data into structured formats, and providing an exceptional customer experience—all while ensuring full transparency and compliance with regulations. This commitment to excellence has made Bright Data an essential tool for organizations seeking to leverage web data for strategic advantages.
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Viktor
Viktor is an AI-powered coworker built to live natively inside Slack and handle complex tasks autonomously. Equipped with its own cloud computer, Viktor can write and execute code, build and deploy applications, analyze metrics, and manage workflows across more than 3,000 integrated tools. It proactively monitors systems, flags issues, and suggests actionable next steps instead of simply responding to prompts. Teams can request reports, create tickets, audit marketing campaigns, or retrieve analytics directly within Slack conversations. Viktor maintains persistent context over long-running projects, coordinating tasks and deadlines across multiple weeks. It connects seamlessly to platforms like Linear, PostHog, Google Ads, and other business tools to automate cross-functional operations. The agent drafts artifacts such as documents, issues, and updates for approval before execution. With both free and enterprise plans, Viktor scales to match team workload and automation needs. Security and workspace controls ensure safe collaboration within organizational environments. By combining autonomy, integrations, and persistent context, Viktor acts as a highly capable digital teammate embedded in daily workflows.
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Calljmp
Calljmp is a developer-first AI runtime for building and running long-lived, stateful agent workflows in production.
Unlike AI agent frameworks that focus mainly on authoring logic in code, Calljmp provides a managed runtime that handles execution concerns by default. This includes durable state persistence, pause and resume for human-in-the-loop workflows, safe retries with idempotency, and built-in observability across every step of an agent’s execution.
Calljmp is designed for teams using TypeScript who want to ship production-grade AI systems without stitching together queues, databases, custom state machines, and monitoring infrastructure. Developers write agent workflows as code, while the runtime guarantees reliable execution over time, even across crashes, restarts, and long waits.
Calljmp targets the gap between developer-first agent frameworks and heavy workflow engines, offering a practical path from prototype to production for real-world AI agents.
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Maisa
Maisa serves as an advanced AI process automation platform that empowers business teams to design, implement, oversee, and enhance dependable AI-driven Digital Workers capable of autonomously handling intricate, decision-making workflows with comprehensive transparency, traceability, and governance. By allowing non-technical staff to articulate objectives and business logic through natural language onboarding, it facilitates the seamless integration of Digital Workers with existing systems, tools, and data sources, including both SaaS applications and legacy systems, without the need for extensive technical assistance. This platform is built with a robust architecture that minimizes hallucinations and logs each action and AI-generated decision, ensuring that automation remains predictable and suitable for mission-critical operations spanning compliance, finance, legal, and operational domains. Furthermore, Maisa Studio embraces a model-agnostic philosophy, enabling organizations to select or transition between AI models without disrupting their automation processes while ensuring enterprise-level governance, scalability, and visibility. Ultimately, Maisa not only streamlines workflow automation but also enhances the overall trust in AI applications across diverse sectors.
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