Peer AI vs Saama (2026)
Peer AI and Saama help medical writers turn study information into regulatory documents. Peer AI centers on authoring and coordination across a submission program; Saama adds document generation to a broader clinical data and study software portfolio. Peer AI Author prepares protocols, study reports, safety narratives and IND content from source files, templates and style guides. Writers inspect supporting material, revise drafts and move DOCX outputs into quality review. Command Center tracks deliverables and dependencies, while Anticipate examines regulatory review patterns. Earlier authoring case results predate those newer orchestration and prediction functions, which have no results of their own. Saama's Document Generator combines multiple language models with templates, reusable prompts and study data. Its TLF Analyzer turns tables, listings and figures into summaries using protocol and statistical analysis plan context, while Medical Lens supports literature investigation. These functions sit beside data quality, data transformation and other clinical modules. Claimed drafting and error reductions lack an attached evaluation method. Peer AI fits regulatory writing teams organizing source grounded drafts and deliverables across a submission program, including deployments in their own AWS environment. Saama fits sponsors and CROs seeking document generation connected to a wider clinical data platform. Both position people as reviewers of generated work before consequential use.
- Regulatory authoring is the central workflow.
- Writers need drafts adapted to organizational templates and style.
- Deliverable dependencies and likely regulatory questions are also in scope.
- Deployment in the customer's AWS environment is desired.
- Document generation should sit beside clinical data management tools.
- Tables and listings need conversion into study report text.
- Teams want reusable prompt and template management.
- Literature investigation should support document design and review.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Peer AI and Saama are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Peer AI | Saama |
|---|---|---|
| Primary category | Clinical Trials AI | Clinical Trials AI |
| Founded | 2023 | Not recorded |
| Headquarters | San Francisco, California, United States | Campbell, California |
| Website | getpeer.ai | saama.com |
Side by Side
Select any grade to read the note behind it.
Each vendor in one paragraph
Written to be quoted whole. Each paragraph opens the AI Health Index profile of the vendor: what the product is, who buys it and what it does.
Peer AI provides regulatory document authoring software for pharmaceutical companies, biotechnology developers, and contract research organizations. Specialized agents prepare protocols, clinical study reports, safety narratives, IND content, and other submission materials from source files and organizational templates.
Source: AI Health Index, October 2026
Campbell, California company selling a clinical data platform and AI modules to pharmaceutical and biotechnology sponsors and contract research organizations.
Source: AI Health Index, October 2026
Questions buyers ask
How are Peer AI and Saama priced and sold?
For Peer AI, the customer can provision or remove access, enable integrations, manage permissions, and control retention and export settings within the arrangement. Deployment can use Peer AI hosting or the customer's AWS environment, and onboarding can include medical writing expertise and adaptation to templates and style guides.
With Saama, enterprise agreements with pharmaceutical and biotechnology sponsors and contract research organizations, sold as platform software and as customized solutions and services, with agents offered as modular additions to a sponsor's existing platforms. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified October 15, 2026. No vendor pays for placement.
How do Peer AI and Saama handle patient data?
In Peer AI's case, the application terms also describe customer control over retention and export settings, indicating that operational document storage and model processing need to be distinguished. Source traceability and medical writer review help detect errors in a draft.
For Saama, the privacy notice (effective 25 Apr 2024) says the company processes pseudonymized trial participant data as a processor for sponsors and contract research organizations, keeps personal information as long as reasonably necessary or as agreed by contract, and may use anonymized data indefinitely. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified October 15, 2026. No vendor pays for placement.
Which settings and specialties do Peer AI and Saama cover?
With Peer AI, an oncology narrative comparison supplies a concrete authoring application, and another case covers a six-part report combining several studies and protocol amendments.
In Saama's case, the clinical platform covers sponsor-side development from study design and startup through conduct, biometrics and submission, and the company also sells commercial, medtech and provider-side products (revenue cycle management, care coordination, hospital orchestration) that sit outside the trial scope this listing describes. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified October 15, 2026. No vendor pays for placement.
What evidence is published for Peer AI and Saama?
For Peer AI, the cases concern authoring, without establishing current performance of the newer program orchestration or query prediction functions.
With Saama, the company reports that customers cut query identification and generation time by as much as 90 percent, study data transformation time by up to 50 percent, and time from data entry to analysis by more than 35 percent, without attributing the figures to a study or giving a method. Its product page illustrates a review of 2,615 queries falling from 1,177 hours to 130 without naming the study. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified October 15, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Clinical Trials AI page.
Peer AI is based in San Francisco and Saama in Campbell, California. Neither has public license amounts or complete implementation prices. Their efficiency claims concern specific workflows, and generated documents still pass through medical writer review.