Why general-purpose AI is not built for medical records

General AI tools are fantastic at many things, from conversation to summarisation. But extracting reliable clinical insight from medical records requires a different level of structure, traceability, governance, and security. Realize-365 is built specifically for that purpose.

Built for long, fragmented patient histories, not short prompts
Designed for structure, consistency, and traceable outputs
Optimised for medical record summarisation and clinical insight, not general conversation
Built with healthcare-grade security and HIPAA-aligned data handling in mind

What are you trying to achieve?

Different AI tools are designed to help with different goals. The key is choosing the tool that matches what you actually need to do.

Raw medical records

Timeline of events

Key findings

Risks and flags

Realize-365 is purpose built to process complex medical records and produce structured summaries and insights with consistency and traceability. It is designed specifically for long patient histories across visits, providers, and formats.

Realize-365 is built for regulated clinical environments where governance, traceability, consistency, and security are foundational requirements. The difference is not just how the tool is used, but the purpose it is built for and the infrastructure required to handle real-world medical records safely and reliably at scale.

What makes this different:

Longitudinal context across the full record
Structured outputs, not just narrative text
Grounding in the underlying medical record
Consistency across teams and workflows

See Realize-365 in action

Clinical interaction

Documentation support

General-purpose AI models are increasingly being adapted for healthcare use. This includes tools designed for the general public as well as tools aimed at supporting clinicians in specific tasks.

These tools typically fall into two groups:

Public-facing health AI, designed to help individuals understand health information, ask questions, or explore symptoms at a high level.
Clinician-facing AI assistants, designed to support specific workflows such as documentation, summarisation, or point-in-time assistance.

Why this is not fit for medical records:

While valuable in their respective contexts, these tools remain general-purpose language models at their core. They are designed around individual interactions or moments in time. They are not built to ingest, reconcile, and interpret complete longitudinal medical records across providers, visits, and formats with consistent structure, traceability, governance, and security.

When to use this:

Use general AI adapted for healthcare for education, conversational assistance, and light summarisation. Use Realize-365 when the goal is to understand the complete medical record as a structured whole.

"What does this mean?"

"This refers to…"

General-purpose AI assistants are designed to help people understand information through conversation. They are excellent at explaining concepts, drafting text, and exploring ideas across many domains.

Why this is not fit for medical records:

Medical records are long, fragmented, and clinically nuanced. Understanding a full patient history safely requires longitudinal context, structured interpretation, and grounding in source data. Conversation alone does not provide those safeguards.

When to use this:

Use these tools for everyday understanding, writing, and exploration.

Long document

Key points summary

Summarisation-first tools are excellent when speed and readability are the priority. They work well for short documents, self-contained reports, and quick overviews where the risk of missing nuance is low.

Why this is not fit for medical records:

Summarisation tools are optimised for short or self-contained documents. Very long documents can exceed practical input limits or lose context across sections. Medical records are not a single document, but a fragmented history across time and providers. Over long histories, nuance and clinically important details can be missed, and there is no built-in mechanism for traceability or structured interpretation.

When to use this:

Use summarisation tools for short content and low-risk overviews.

"Find prior MRI"

Relevant excerpts

Search and retrieval systems are designed to surface relevant information efficiently. They are excellent for discovery, reference, and research workflows.

Why this is not fit for medical records:

Finding information is not the same as understanding a patient. Clinical insight requires coherent timelines and structured interpretation across visits, providers, and formats.

When to use this:

Use retrieval tools to locate information and references.

Manual steps

Automated workflow

Automation and productivity tools are designed to reduce repetitive work and connect systems. They save time and improve efficiency across many environments.

Why this is not fit for medical records:

Automation accelerates workflows, but it does not interpret complex clinical history. Medical records require structured understanding and careful summarisation.

When to use this:

Use automation tools to streamline processes and reduce administrative overhead.

How Realize-365 works

Realize-365 processes complex medical records through a purpose-built pipeline designed for clinical accuracy and operational reliability.

The Realize-365 approach

1
Ingests records across formats, providers, and time periods
2
Builds a longitudinal view of the patient's clinical history
3
Extracts structured data points, not just narrative summaries
4
Grounds every insight in the underlying source material
5
Delivers consistent outputs across different users and workflows

What you get

Structured summaries organised by clinical category
Chronological timelines of key events and findings
Highlighted gaps, contradictions, and critical details
Traceable links back to the original record
Outputs ready for integration into clinical workflows

Realize-365 is designed for regulated clinical workflows where governance, traceability, and consistency are essential. The difference is not just how the tool is used. It is the purpose it is built for, and the infrastructure required to handle real-world medical records safely and reliably at scale.

Realize-365 is not a general AI assistant. It is healthcare-grade infrastructure for medical record intelligence.

Built by clinicians and engineers who understand what clinical workflows actually require.

See Realize-365 in action

If you are evaluating AI for medical record summarisation, we can show you exactly how Realize-365 handles real-world records and workflows.

Book a demo

Have more questions? Visit our FAQ

Why general-purpose AI is not built for medical records

What are you trying to achieve?

Understand complex medical records

General AI for healthcare use

Explain or discuss information

Summarise text quickly

Find information across documents

Automate repetitive work

How Realize-365 works

The Realize-365 approach

What you get

See Realize-365 in action