Accountability for AI copilots
Existing workflow support tools for inventory rebalancing, managerial approvals, or call center interactions can all benefit from AI copilots to streamline routine operations and improve the quality of service for tasks that need human attention. The benefit of automating common cases shows up as reduced wait times and lower operating costs. But giving a machine control of management decisions is risky, and you donât want to be in the dark about the decisions AI is making or recommending in the field.
Fireproof is the ideal database for capturing interactive user and AI agent behavior in web applications. Fireproofâs flexible schema and indelible event tracking make it easy to use as part of your app development process, with a result that allows AI safety and app design teams to replay sessions and understand application behavior in the wild. For a deeper, more technical exploration of how to improve AI authenticity, efficiency and reliability, take a look at Why proofs matter for AI.
Fireproof is designed for compatibility with any web app, so it fits securely in your existing context â you can add it to your project just like any other JavaScript package. It supports pluggable backends with common connectors, so working within your production-tested environment is easy. Thatâs just the beginning â once Fireproof is instantiated in every application instance, it unlocks powerful new capabilities. Read about one great example: running real-time analytics queries across live session data.
The combination of provable event logs and multi-writer live interaction makes Fireproof a good fit for workflows like real-time distributed analytics, ride-hailing sessions, live contract configurators, and quality control, in addition to supporting AI copilot safety. When you add verifiable CRDTs in the mix, it unlocks the ability to dramatically simplify the architecture of most any SaaS or web application.
By using Fireproof as an interaction database, you simplify your architecture by isolating user interaction data from core data, while giving you provable data integrity and the ability to replay sessions. Fireproof runs on cost-effective commodity storage APIs, so you can usually get it running using your existing infrastructure. This makes it cheap and easy to monitor AI copilots in the wild, while giving your developers a powerful new option for feature development.