Raw text of multiple legal agreements
AI Models & Assistants / Knowledge library
o1 Preview
Preview of our first o-series reasoning model
Why learn o1 Preview?
Offers the documented OpenAI model capabilities through hosted.
The problem it solves
Provides model inference for supported text inputs.
Where it came from
o1 Preview: Preview of our first o-series reasoning model Published aliases: o1-preview-2024-09-12. Input: text. Output: text. Checked 2026-10-13. Model capabilities are distinct from tools available in a particular agent.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain what o1 Preview does.
- Identify a use case for o1 Preview.
- Describe a limitation of o1 Preview.
- Name a compatible tool for o1 Preview.
- Compare o1 Preview against an alternative.
Documentation and sources
- Primary source / model card (developers.openai.com)
Catalog research notes
- See the AI Workbench for source dates, pricing evidence and configuration details.
Connect the ideas
Built on
Real World Example
Automated Legal Clause Reconciliation
Corporate legal departments managing complex cross-border contract portfolios.
The business problem
Standard LLMs frequently hallucinate or misinterpret subtle contradictions between overlapping contract clauses, leading to high manual review costs and potential compliance risks.
How this topic solves it
The o1-preview model utilizes an internal chain of thought to perform deep logical verification of contract clauses before generating a final reconciliation report, ensuring that dependencies and conflicting obligations are identified through rigorous reasoning.
- Ingest raw contract text into the Chat Completions endpoint using the o1-preview model ID.
- Define a system prompt that instructs the model to explicitly map dependencies between clauses.
- Execute the completion request, allowing the model to generate its internal chain of thought.
- Parse the final output to extract structured reconciliation findings for the legal team.
This diagram illustrates how legal documents are processed through the o1-preview reasoning pipeline.
Performs internal chain of thought reasoning
Structured list of identified conflicts
- Contract Input → Submit via Chat Completions → o1-preview Engine
- o1-preview Engine → Output verified findings → Reconciliation Report
Expected business outcome
Legal teams receive a high-fidelity summary of clause conflicts, significantly reducing the time spent on initial document cross-referencing.
Limitations and checks
The model's reliance on extensive internal reasoning can lead to increased latency compared to standard models; developers should monitor response times to ensure they meet user experience requirements.