Advanced AI Agent Training
Boosting Search Agent Performance with InfoFlow
InfoFlow tackles low reward density in deep search, enhancing LLM agent performance through sub-goal scaffolding, pathfinding hints, and dual-agent refinement for more efficient and accurate knowledge discovery.
Executive Impact
InfoFlow significantly improves the efficiency and accuracy of AI agents in complex deep search tasks, leading to substantial gains in operational effectiveness and decision-making speed.
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Higher Initial Rewards
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Shorter Trajectories
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Increased Accuracy
By optimizing reward density and refining search trajectories, InfoFlow enables more robust and scalable AI agent deployments for critical enterprise applications.
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
InfoFlow introduces Reward Density Optimization to address the challenge of low reward density in deep search scenarios. This involves maximizing reward per unit of exploration cost, making learning more efficient for LLM agents.
Key mechanisms include Sub-goal Scaffolding for denser learning signals, Pathfinding Hints for corrective guidance, and Dual-agent Refinement to reduce cognitive burden.
The framework employs a Researcher Agent for planning and exploration and a Refiner Agent for synthesizing retrieved evidence into concise summaries. This decoupling enhances reward density and reduces the context length for the researcher.
This collaboration improves efficiency and accuracy, allowing lightweight LLMs to perform comparably to advanced proprietary models.
InfoFlow leverages Reinforcement Learning with Verifiable Rewards (RLVR) to train LLM agents for agentic deep search. RL is crucial for learning robust search policies, especially in complex, multi-step tasks.
The framework includes Group Relative Policy Optimization (GRPO) to normalize advantages and reduce variance during training.
59.5%
Higher Initial Rewards with Dual-Agent Refinement
Enterprise Process Flow
Complex Deep Search Query
→
Subproblem Decomposition (Sub-goals)
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Researcher Agent (Planning & Exploration)
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Refiner Agent (Evidence Synthesis)
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Pathfinding Hints (Corrective Guidance)
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Reward Density Optimization
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Final Answer
| Feature | InfoFlow Solution | Traditional RLVR |
|---|---|---|
| Reward Density | High (process-level) | Low (sparse final reward) |
| Learning Signal | Dense & structured | Infrequent |
| Exploration Efficiency | Guided & adaptive | Unproductive loops |
| Cognitive Burden | Reduced (dual-agent) | High (single agent) |
Performance on BrowseComp-Plus Benchmark
InfoFlow-7B significantly outperforms strong baselines, including much larger LLMs, on the challenging BrowseComp-Plus benchmark. This demonstrates its efficacy in handling complex, long-horizon deep search tasks requiring iterative reasoning and information synthesis.
- InfoFlow-7B achieves 23.2% accuracy.
- Outperforms Gemini 2.5 Pro (19.0%) and GPT-4.1 (14.6%).
- Enables lightweight LLMs to achieve performance competitive with advanced proprietary LLMs.
Calculate Your Potential ROI
Estimate the efficiency gains and cost savings your enterprise could achieve with InfoFlow.
Estimated Annual Savings
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Annual Hours Reclaimed
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Your InfoFlow Implementation Roadmap
A phased approach to integrating InfoFlow into your enterprise workflows for maximum impact and smooth transition.
01 Pilot Program & Integration
Implement InfoFlow in a controlled environment, integrating with existing search infrastructure and validating initial performance metrics. (Weeks 1-4)
02 Full-Scale Deployment & Training
Scale InfoFlow across enterprise search tasks, continuously training and refining agents with real-world data to maximize reward density and accuracy. (Months 2-6)
03 Continuous Optimization & Expansion
Monitor agent performance, identify new use cases, and expand InfoFlow's application to broader knowledge discovery and synthesis workflows. (Ongoing)
Ready to Transform Your Research?
Schedule a personalized consultation with our AI experts to explore how InfoFlow can revolutionize your enterprise's knowledge discovery.
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