Free
$0/mo
- 100 learnings generated / month
- 1,000 search requests / month
- 30-day Pro trial
- Community support
Overview
Reflexio addresses the challenge of AI agents repeating mistakes by capturing user corrections and transforming them into actionable rules. This process ensures that agents continuously improve their performance over time.
How Reflexio Works
The platform ingests data from instrumented tracing platforms or direct application publishing, analyzing execution paths, tool calls, and user corrections. An intelligence engine then extracts recurring failures and synthesizes actionable execution rules. These rules are retrieved by the agent before its next execution, facilitating continuous learning and enhancing tool reliability.
Key Benefits
- Reduces execution failures by eliminating repeat tool errors and invalid execution paths.
- Prevents redundant reasoning and tool calls, optimizing token usage.
- Decreases execution latency by providing relevant context before an agent responds.
Agents can integrate Reflexio through a portable skill, Python, TypeScript, REST, or the CLI, offering flexible deployment into existing agent lifecycles. The platform also provides enterprise-grade governance, allowing complete controllability over learned rules, visible learning insights, and instant retrievability of data. Users can inspect, edit, or reject learnings to maintain control. Reflexio supports various deployment options, from a fully managed cloud service to self-hosted within a user's VPC, ensuring data sovereignty and compliance.
Key features
- Captures user corrections and turns them into rules
- Eliminates repeat tool errors and invalid execution paths
- Prevents redundant reasoning and tool calls
- Reduces execution latency by providing context
- Inspects and manages learned rules in a portal
- Supports flexible integration via SDK, REST, CLI
- Offers fully managed to self-hosted deployment options
- Provides visible learning insights and instant data retrievability
Who uses it
Developers, AI engineers, and teams building and managing AI agents.
Pros
- Enables AI agents to learn from past interactions and avoid repeating mistakes.
- Reduces operational costs by decreasing token usage and execution latency.
- Offers flexible integration options with existing agent frameworks and languages.
- Provides comprehensive control and visibility over the agent's learning process.
- Supports various deployment models, including self-hosted for data sovereignty.
Cons
- Specific pricing tiers and features are not transparently listed on the website.
- Requires integration into existing agent applications, which may involve a setup process.
- The platform's full capabilities might require a technical understanding of AI agent lifecycles.
- No dedicated mobile or desktop application is mentioned for management.
Our take
Reflexio offers a practical solution for enhancing AI agent reliability and efficiency by systematically capturing and applying learned behaviors. It provides developers with tools to manage and improve agent performance through continuous feedback loops.
Pricing plans
Pro
$299/mo
- 10K learnings generated / month
- 100K search requests / month
- Overage: 0.3¢ per search request, 2¢ per playbook learning, 1¢ per profile learning
- Priority support
BYOC
Custom
- Self-host in your own AWS, GCP, or Azure
- Your data never leaves your infrastructure
- Bring your own LLM and storage
- Configurable data retention
- Dedicated support & onboarding
Pricing details are provided for reference and may differ from the vendor's current plans.
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