# Concord vs Ironclad: which do AI models recommend for CLM, October 2026

GTM AI Recommendation Index, October 2026 Edition, Contract lifecycle management and e-signature. Three of fourteen models named Concord first on the direct prompt; five named Ironclad. Page: https://gtm-ai-index.com/revops/contract-lifecycle-management-and-e-signature/concord-vs-ironclad/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Concord | 19% | #2 of 15 | 3% | 35 | 13 of 14 |
| Ironclad | 15% | #4 of 15 | 20% | 59 | 14 of 14 |

## The direct prompt, model by model

- MiniMax M2.5: both first (first choices: Concord, Ironclad, Juro) (alternatives: DocuSign CLM, PandaDoc)
- Claude Haiku 4.5: concord first (first choices: Concord) (alternatives: Ironclad, LinkSquares)
- Mistral Small: concord first (first choices: Concord) (alternatives: Conga CLM, Ironclad)
- GPT-5.4 mini: ironclad first (first choices: Ironclad) (alternatives: Conga CLM, DocuSign CLM)
- Gemini 3.5 Flash: ironclad first (first choices: Ironclad) (alternatives: Gatekeeper, Juro, LinkSquares)
- Grok 4.1 Fast: ironclad first (first choices: Ironclad) (alternatives: Concord, Juro)
- Muse Glimmer 30B: ironclad first (first choices: Ironclad) (alternatives: Agiloft, Concord)
- Perplexity Sonar: neither first, one named (first choices: Juro) (alternatives: Ironclad, Oneflow)
- DeepSeek V4 Flash: neither first, one named (first choices: Juro) (alternatives: Concord, DocuSign CLM, LinkSquares, PandaDoc)
- Qwen 3.7 Flash: neither first, one named (first choices: Juro) (alternatives: Ironclad, PandaDoc)
- Kimi K2: neither first, one named (first choices: DocuSign CLM) (alternatives: Concord, Ironclad, LinkSquares)
- GLM 4.7 FlashX: neither first, one named (first choices: Juro) (alternatives: Concord, PandaDoc)
- GPT-6 Luna: neither first, one named (first choices: Juro) (alternatives: Ironclad, LinkSquares, SpotDraft)
- Llama 4 Maverick: neither named (first choices: Juro) (alternatives: Conga CLM, Oneflow)

## What the models said about Concord

- ""The very small team (~22 employees) raises questions about support and migration capacity"" (Muse Glimmer 30B, negative prompt, soft negative)
- "The best contract lifecycle management platform for a company with a limited budget is Concord, which has an entry tier priced at $499." (Llama 4 Maverick, budget prompt, first choice)
- "If you have 3–5 people and want simplicity: Concord ($499/month flat) is hard to beat for predictable costs and true CLM features." (Kimi K2, budget prompt, first choice)
- "For a balance of affordability, ease of use, and mid-market focus, Concord is often the top recommendation." (Mistral Small, direct prompt, first choice)

## What the models said about Ironclad

- "Avoid vendors like Ironclad, Agiloft, Icertis, and ContractPodAI if budget predictability matters" (Kimi K2, budget prompt, hard negative)
- "Avoid if you need granular security: Ironclad (current security gaps)." (GLM 4.7 FlashX, negative prompt, hard negative)
- "Enterprise suites with long implementations and premium pricing: platforms like Ironclad, DocuSign CLM, Conga, Icertis, and Sirion can be the wrong fit" (Perplexity Sonar, negative prompt, soft negative)
- "aim for mid-market tools like Ironclad, Conga CLM, LinkSquares, Sirion, Agiloft, or SpotDraft... Ironclad/Conga: Workflow-first, Salesforce-heavy, great for sales/legal speed." (Grok 4.1 Fast, scale prompt, first choice)
- "Ironclad - AI-powered drafting, workflow automation, strong Salesforce integration. Best for mid-market to enterprise legal/sales teams" (Grok 4.1 Fast, comparative prompt, first choice)
- "Most enterprise buyers shortlist Icertis (for AI/governance), Ironclad (for workflow UX), and Sirion" (DeepSeek V4 Flash, comparative prompt, first choice)

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.