nekuda vs. Graft

Nekuda revolutionizes websites by converting them into interactive platforms where AI agents can effectively operate, utilizing WebMCP tools that allow for various site functions while giving website owners the ability to oversee and manage these interactions. Development teams can either build extensive WebMCP tools with a coding agent or quickly initiate basic tools by adding a single line of code to their public website. After implementing these tools, businesses are empowered to specify and monitor the actions that agents can take, including essential tasks such as product searches, retrieving policies, managing checkout processes, tracking orders, and updating application data. Furthermore, Nekuda meticulously tracks agent activities, logging each interaction with tools and entire sessions, thus providing teams with valuable insights into the navigation patterns of agents on their website. The platform also incorporates robust evaluation and testing functionalities that measure task success rates, enabling the replaying of scenarios both before and after deployment to confirm that critical workflows like searching, checkout, policy retrieval, and fallback actions function seamlessly and as anticipated. This holistic strategy not only boosts website functionality but also equips teams with the ability to continually adapt and refine their digital landscapes informed by real-time data and agent performance insights, fostering an environment ripe for innovation and improvement. In this way, Nekuda ensures that businesses can meet evolving user needs while maintaining high standards of operational excellence.

Graft AI is a platform for helping AI agents safely use the legacy software that businesses already depend on. It turns real application interfaces into stable tools, allowing agents to execute workflows without requiring source-system replacement or new APIs. Graft is built for systems such as ERPs, mainframes, desktop apps, web portals, virtual desktops, internal applications, custom systems, and file-based workflows. The platform observes real workflows and maps screens, inputs, transitions, rules, side effects, and interface states. It then compiles those workflows into typed schemas, adapters, policy boundaries, recovery behavior, idempotency rules, and conformance tests. Agents can call the resulting stable MCP tools instead of rediscovering and navigating the interface from scratch each time. Graft verifies source-system effects through independent evidence, such as source records or generated IDs, so actions can be proven rather than assumed. Policy controls enforce approvals, roles, boundaries, least-privilege access, and permission-aware execution before agents make changes. Every action is logged with full context, giving teams a complete audit trail across workflows such as order creation, invoice processing, customer updates, ticket creation, reconciliation, reporting, and support operations. The platform runs in the customer’s environment, keeps data under customer control, and states that customer data does not train its models. By combining interface mapping, stable tool contracts, governed execution, source-effect verification, audit trails, and agent framework compatibility, Graft AI helps enterprises extend AI agents into the systems they cannot replace.