--- title: "deepteam vs ai-berkshire" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/confident-ai-deepteam-vs-xbtlin-ai-berkshire" tools: ["confident-ai-deepteam", "xbtlin-ai-berkshire"] --- # deepteam vs ai-berkshire *GraphCanon updated Sep 20, 2026* ## Verdict Pick deepteam if deepTeam is a tool to assess security and safety in LLMs and AI agents through an implementation of guardrails; pick ai-berkshire if ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's. [deepteam](https://trydeepteam.com) reports 2.8k GitHub stars, 449 forks, and 64 open issues, last pushed Aug 21, 2026. [ai-berkshire](https://github.com/xbtlin/ai-berkshire#readme) has 16k stars, 2.5k forks, and 39 open issues, last pushed Sep 19, 2026. Figures are from public GitHub metadata via [deepteam's repository](https://github.com/confident-ai/deepteam) and [ai-berkshire's repository](https://github.com/xbtlin/ai-berkshire). | | [deepteam](/tools/confident-ai-deepteam.md) | [ai-berkshire](/tools/xbtlin-ai-berkshire.md) | | --- | --- | --- | | Tagline | Framework to red team LLMs and AI agents | AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis. | | Stars | 2,789 | 16,451 | | Forks | 449 | 2,456 | | Open issues | 64 | 39 | | Language | Python | HTML | | Adopt for | DeepTeam is a tool to assess security and safety in LLMs and AI agents through an implementation of guardrails. | ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [deepteam](/tools/confident-ai-deepteam.md) | [ai-berkshire](/tools/xbtlin-ai-berkshire.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 23d | 0d | | Open issues (now) | 64 | 39 | | Stars delta | +388 (30d) | +2.3k (30d) | | Open issues delta | +11 (30d) | +10 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/confident-ai-deepteam/trust.md) | [trust report](/tools/xbtlin-ai-berkshire/trust.md) | ## Decision facts: deepteam - **Pricing:** freemium - Free to use and modify under the terms of its Apache 2.0 license, encouraging community contribution and adaptation - **Requirements:** Min 4 GB RAM; Requires a Python environment.; No Docker required for operation. - **Adopt for:** DeepTeam is a tool to assess security and safety in LLMs and AI agents through an implementation of guardrails. ## Decision facts: ai-berkshire - **Adopt for:** ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's ## Choose when ### Choose deepteam if… - deepteam is primarily Python; ai-berkshire is HTML. - License: deepteam is Apache-2.0, ai-berkshire is MIT. - Pricing: Free to use and modify under the terms of its Apache 2.0 license, encouraging community contribution and adaptation. - Requirements: Min 4 GB RAM; Requires a Python environment.; No Docker required for operation.. - Tags unique to deepteam: apache 2.0, llm-guardrails, llm-red-teaming, llm-safety. - When you need a framework specifically designed for red-teaming large language models and AI agents under the Apache-2.0 license. ### Choose ai-berkshire if… - ai-berkshire is primarily HTML; deepteam is Python. - License: ai-berkshire is MIT, deepteam is Apache-2.0. - Tags unique to ai-berkshire: ai, financial-analysis, investment-research, portfolio-management. - Also covers AI Agents. - You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies. ## When NOT to use deepteam - If your team requires proprietary or more restrictive licensing conditions, given DeepTeam operates under an open-source Apache-2.0 license. - When you are working with non-Python programming environments as DeepTeam is only supported in Python. ## When NOT to use ai-berkshire - If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise. - When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies. ## Common questions ### What is the difference between deepteam and ai-berkshire? deepteam: Framework to red team LLMs and AI agents. ai-berkshire: AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis.. See the comparison table for live GitHub stats and shared categories. ### When should I choose deepteam over ai-berkshire? Choose deepteam over ai-berkshire when deepteam is primarily Python; ai-berkshire is HTML; License: deepteam is Apache-2.0, ai-berkshire is MIT; Pricing: Free to use and modify under the terms of its Apache 2.0 license, encouraging community contribution and adaptation; Requirements: Min 4 GB RAM; Requires a Python environment.; No Docker required for operation.; Tags unique to deepteam: apache 2.0, llm-guardrails, llm-red-teaming, llm-safety; When you need a framework specifically designed for red-teaming large language models and AI agents under the Apache-2.0 license. ### When should I choose ai-berkshire over deepteam? Choose ai-berkshire over deepteam when ai-berkshire is primarily HTML; deepteam is Python; License: ai-berkshire is MIT, deepteam is Apache-2.0; Tags unique to ai-berkshire: ai, financial-analysis, investment-research, portfolio-management; Also covers AI Agents; You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies. ### When should I avoid deepteam? If your team requires proprietary or more restrictive licensing conditions, given DeepTeam operates under an open-source Apache-2.0 license. When you are working with non-Python programming environments as DeepTeam is only supported in Python. ### When should I avoid ai-berkshire? If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise. When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies. ### Is deepteam or ai-berkshire more popular on GitHub? ai-berkshire has more GitHub stars (16,451 vs 2,789). Stars measure visibility, not whether either tool fits your constraints. ### Are deepteam and ai-berkshire open source? Yes - both are open-source projects on GitHub (deepteam: Apache-2.0, ai-berkshire: MIT). ### Where can I find alternatives to deepteam or ai-berkshire? GraphCanon lists graph-backed alternatives at [deepteam alternatives](/tools/confident-ai-deepteam/alternatives) and [ai-berkshire alternatives](/tools/xbtlin-ai-berkshire/alternatives) ([deepteam markdown twin](/tools/confident-ai-deepteam/alternatives.md), [ai-berkshire markdown twin](/tools/xbtlin-ai-berkshire/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/confident-ai-deepteam-vs-xbtlin-ai-berkshire.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, deepteam or ai-berkshire? deepteam: Active. ai-berkshire: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for deepteam and ai-berkshire? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [deepteam trust report](/tools/confident-ai-deepteam/trust); [ai-berkshire trust report](/tools/xbtlin-ai-berkshire/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=confident-ai-deepteam`](/api/graphcanon/graph?tool=confident-ai-deepteam) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_