Startup spotlight: building AI agents and accelerating innovation with Cohort #5

With quick access to flexible infrastructure and innovative AI tools, startups are able to deploy production-ready applications with speed and efficiency. Cloudflare plays a pivotal role for countless applications, empowering founders and engineering teams to build, scale, and accelerate their innovations with ease — and without the burden of technical overhead. And when applicable, initiatives like our Startup Program and Workers Launchpad offer the tooling and resources that further fuel these ambitious projects.

Cloudflare recently announced AI agents, allowing developers to leverage Cloudflare to deploy agents to complete autonomous tasks. We’re already seeing some great examples of startups leveraging Cloudflare as their platform of choice to invest in building their agent infrastructure. Read on to see how a few up-and-coming startups are building their AI agent platforms, powered by Cloudflare.

Founded in 2023, Lamatic.ai empowers SaaS startups to seamlessly integrate intelligent AI agents into their products. Lamatic.ai simplifies the deployment of AI agents by offering a fully managed lifecycle with scalability and security in mind. SaaS providers have been leveraging Lamatic to replatform their AI workflows via a no-code visual builder to reduce technical debt and ship products faster. Designed for high availability, scalability, and low latency, Lamatic’s architecture enables developers to build AI-driven applications that remain performant under heavy load. After acquiring a high amount of users in a short amount of time on Product Hunt, Lamatic identified there was real interest to solve complex problems with AI Agents, and the team knew they needed to build a solution with scalability and performance in mind.

Cloudflare plays a key role in supporting Lamatic’s growth. Powered by Cloudflare Workers, Lamatic ensures requests process closer to end users, minimizing latency while offloading computational strain from centralized servers. In just a few months, Lamatic.ai has efficiently scaled to over three million serverless requests per month, supporting over 1,000 customers — all managed by a lean three-person team. 

Customers design their Agent Flows through a no-code visual builder, which generates an interoperable YAML configuration. Sensitive credentials such as API keys and model access tokens are securely encrypted and stored in Workers KV, ensuring they are only decrypted at runtime for enhanced security. All YAML configurations are then compiled into a Workers-compatible JavaScript bundle. When a project is deployed, Lamatic orchestrates critical components like sync jobs for scheduled data ETL operations and incoming webhooks to handle event-driven workflows via Cloudflare Queues. Once deployed, the project is fully operational as a Cloudflare Worker with an exposed API endpoint, allowing customers to integrate AI-powered automation directly into their applications with minimal friction.

To scale out their platform, Lamatic.ai built their architecture isolating serverless and AI logic on a per-customer basis. Rather than batching requests into a centralized cluster, Lamatic.ai distributes workloads across Cloudflare’s global network, ensuring each customer and endpoint is served by its own Worker executing dedicated logic. This per-customer deployment model — enabled by Workers for Platforms — allows Lamatic.ai to deliver customer-specific serverless functions at scale, and reduces technical overhead as they onboard additional customers. Each customer gets a dedicated Worker whose request and rate limits are enabled based on their level of subscription. 

Beyond request processing, Lamatic uses Cloudflare Workers KV as a distributed config store to ensure high availability and security. All values are encrypted at rest with AES-256-GCM and decrypted only at runtime, keeping operations both secure and low-latency. Tokens and user credentials are encrypted and stored in the database and KV. 

To further enhance performance, Cloudflare Queues plays a key role in orchestrating task completion. Lamatic uses Queues to offload work from Workers requests, and handle tasks such as webhooks and coordinating distributed processes, both essential for maintaining system consistency and reliability at scale. While Workers handle sync requests at point of execution, longer running jobs process via Queues. For example, during a scheduled ETL sync, new data records generated are stored as a message queue on Cloudflare Pub/Sub. A consumer Worker collects these messages and makes an API request to the pod using the Workers Queue. The consumer Worker consumes more messages as each queue is finished processing.

Another example of where this has been optimal is for managing AI workflows. Many AI workflows involve concurrent requests to multiple data sources, Queues streamlines data processing and efficiently feeds information into customers’ Retrieval Augmented Generation (RAG) workflows. This approach smooths out workload spikes, reduces bottlenecks, and ensures that AI agents can reliably aggregate and process data without delays.

Beyond this, Lamatic.ai offers Workers AI as one of the support inference providers that customers can use across their platform. Customers can choose to run one of the many open source models hosted on Workers AI, depending on their use case (chatbot, image generation, voice, etc.). Together, these layers solve the challenges of scaling AI agents by handling high volumes of data, maintaining low-latency responses, and ensuring robust security. With Cloudflare’s infrastructure as its backbone, Lamatic.ai has built a resilient and high-performing platform that meets the rigorous demands of modern AI applications, making it an ideal choice for startups embedding AI-driven features into their products.

Skyward AI is transforming compliance operations by leveraging Cloudflare’s serverless computing capabilities to build AI-driven compliance agents that streamline critical tasks like evidence collection, real-time risk analysis, and policy updates. Compliance teams in fintech, supply chain, and other highly regulated industries use these AI Agents to extract and organize evidence, provide real-time recommendations, and orchestrate policy and procedural updates automatically. By handling document parsing, risk monitoring, and policy enforcement, these AI Agents reduce the risk of human error while allowing compliance professionals to focus on high-value tasks.

Skyward has built an AI agents platform designed with a serverless-first approach, avoiding the constraints of centralized cloud computing. To achieve this, the company leverages Cloudflare’s Developer Platform to create and maintain a highly responsive and scalable infrastructure. Workers handle incoming requests like chat inputs, compliance checks, or authentication, and route them efficiently across multiple geographies. Skyward initially built their AI agents infrastructure using Durable Objects, Workflows and JavaScript-native RPC for AI coordination, but has recently transitioned to Cloudflare’s new AI agents framework. Given that agents provides a framework for building and orchestrating AI agents, the migration has helped Skyward abstract the need to manage Durable Objects manually, significantly reducing time spent on managing these tools. While this release is fairly recent, the transition has helped simplify the way that agents communicate, but it also preserved the benefits of their original design like data privacy, isolation, and concurrency management. This has also made it easier to provide real-time feedback and responses to their end users.

Skyward optimizes real-time compliance automation by achieving sub-100 ms response times for AI agent queries. Workloads are structured to minimize unnecessary network round-trips, and a sync-engine approach proactively preloads and pushes data to clients, delivering a highly responsive user experience. To proxy AI inference, Skyward uses AI Gateway to provide observability into usage, performance, and costs across multiple vendors, improving their AI operational efficiency. Leveraging Cloudflare’s serverless Developer Platform has allowed Skyward to simplify their architecture while supporting global availability, avoiding the need for Kubernetes clusters or complex locking mechanisms. The team also avoids the burden of managing regional deployments, as Cloudflare’s multi-region support ensures consistent performance worldwide without added operational complexity.

State management is a critical component to execute agentic workflows. Each compliance session runs within a dedicated Durable Object, which keeps relevant data close to the execution layer. This setup minimizes database round-trips and ensures that tasks like Anti-Money Laundering (AML) checks, Know Your Business (KYB) validation, and document processing remain efficient. Once a compliance session is complete, the system summarizes and stores the relevant information in Postgres and R2, optimizing memory usage without requiring persistent cloud infrastructure.

To balance low-latency operations with long-term storage, Skyward employs a multi-layered data management strategy. The Skyward team, using Hyperdrive, has been able to reduce query latency by nearly 50%, allowing compliance teams to receive immediate feedback. At the company's core, Skyward’s goal is to offer a platform that is "streamlined for compliance teams”. The team maintains that a speedy feedback loop ensures end customers get the data and responses needed to act. Whether there's one agent or hundreds of agents processing tasks in parallel, Hyperdrive ensures that database requests to assets like extensive company documentation (i.e. regulations, policies, procedures, internal documents), complex regulatory knowledge graphs, and on-demand context information for conversational workflows are all as performant as possible.

Durable Objects facilitate real-time session state, ensuring AI agents function smoothly without complex locking mechanisms. For larger compliance-related documents, such as legal PDFs and archived data, Cloudflare R2 provides long-term storage, ensuring only frequently accessed information remains readily available. This approach enhances performance while keeping storage management efficient and cost-effective.

Security and scalability remain priorities for compliance-focused AI applications. Skyward enforces strict access controls, ensuring that only authorized users can access development and production environments. Each AI session maintains an auditable log of key events, user actions, and approvals, supporting the ability to export these insights for compliance and legal requirements. Because each agent is deployed in its own instance and has its own database, Skyward ensures that there is a detailed record of every required user, agent interaction, and auditing requirements. On top of this, the ability to deploy and scale globally with Cloudflare’s network has allowed Skyward to maintain consistent, high-performance operations across multiple regions without extensive infrastructure overhead.

Looking ahead, Skyward plans to further enhance AI agent responsiveness by running select models directly on Cloudflare Workers AI, reducing reliance on external inference providers. The team plans to further integrate Workers for Platforms in an effort to better isolate customer data and workflows, giving end users greater control over their compliance automation. As Cloudflare continues to evolve its AI capabilities, Skyward aims to push the boundaries of distributed AI compliance solutions, making regulatory adherence more automated, scalable, and secure.

We’re inspired by how startups like Lamatic AI and Skyward AI are building their AI agent platforms on Cloudflare. This kind of innovation is why we’re proud to see so many startups trust Cloudflare for a scalable, reliable, and efficient foundation. 

We’re also thrilled to share that both Lamatic AI and Skyward AI have been invited to join Cloudflare’s upcoming Workers Launchpad Cohort #5. Speaking of Workers Launchpad, it’s been a few months since our last update — let’s take a look at what’s new.

The Workers Launchpad team is blown away by what customers are demonstrating on the Developer Platform. Members of Cohort #4 presented at our bi-annual Demo Day. We had customers demonstrate what they’re building across a multitude of industries, including (of course) AI / ML, developer tools, 3D design, cloud infrastructure, adtech, media, and beyond. It’s incredibly encouraging to see what all these amazing companies are building on the Cloudflare network, and we look forward to continuing to partner with them throughout their startup journey.

Following the Demo Day for Workers Launchpad Cohort #4, we’ve seen the largest influx of applications from startups across the globe eager to join Cohort #5. This next wave of founders is pushing the boundaries of what’s possible, building in areas like AI agents, developer tooling, MCP, media, and beyond. With each new cohort, we’re continually inspired by the caliber of founding teams, the bold ideas they bring to life, and the real-world problems they’re tackling with technology.

Help us give some love and a warm welcome to the participants of Cohort #5:

We can’t wait to share more about what Cohort #5 achieves. Be sure to follow @CloudflareDev on X and join our Developer Discord server to hear updates on the cohorts.

If you’re developing your application on our Developer Platform, we’d love to learn how Cloudflare is powering your journey. Please share more about what you’re building, and our team will be sure to review your submission. And if you’re a startup and interested in joining Workers Launchpad, feel free to apply for Cohort 6 — applications are now open!