On-premise healthcare AI
We set up and maintain on-premise and locally hosted AI workflows for clinics, hospitals, and healthcare operators that need transcription, document analysis, internal search, or workflow automation without pushing patient data to public AI services.
For many healthcare teams, cloud AI is not the real blocker. The blocker is sending PHI outside the network. We deploy models where your compliance, legal, and security teams are comfortable.
Real-time transcription, note drafting, and local search are more useful when they respond quickly and do not depend on an outside API staying available.
Model choice, retention policy, logging, network access, backup strategy, and upgrade timing stay under your control instead of being dictated by a third-party AI vendor roadmap.
This is not limited to one model or one box. We can design smaller local setups for a clinic, department-level deployments for a provider group, or more robust infrastructure for higher-volume workloads.
Doctors, nurses, scribes, care coordinators
Private speech-to-text pipelines, ambient visit capture, encounter summarization, SOAP note drafting, and review-first documentation flows that can run inside your own network.
Operations, admin, HIM, billing, intake
Search, summarize, classify, and extract information from referrals, scanned forms, discharge notes, policies, lab documents, and payer paperwork without shipping files to external AI APIs.
Call centers, front desk teams, patient support
On-site chat and voice assistants for scheduling, FAQs, handoff prep, policy lookup, and internal knowledge support, with clear escalation rules and no dependence on public chat services.
Department leads, quality teams, innovation groups
Deploy private models for cohort analysis, de-identified reporting support, document triage, coding assistance, and internal workflow automation where cloud usage is restricted or politically difficult.
Healthcare teams usually do not need another AI proof-of-concept. They need a usable private system with clear boundaries, a sensible deployment plan, and someone accountable for keeping it healthy over time.
Step 01
We start by identifying what data is involved, where it lives, who touches it, and which use cases are safe enough to automate. If on-prem is the wrong answer, we say so.
Step 02
We recommend the model class, inference setup, storage pattern, observability, security controls, and integration points for your EHR-adjacent or operational workflow.
Step 03
We install the environment, connect it to the right internal systems, define access controls, and make the workflow usable for real teams rather than leaving you with raw infrastructure.
Step 04
We handle upgrades, patching, monitoring, evaluation, prompt and workflow tuning, and the operational maintenance needed to keep the system dependable after launch.
You pay Zee Palm for planning, deployment, integrations, workflow implementation, security hardening, and ongoing support. We are not reselling GPUs or inflating hardware quotes.
Servers, GPUs, storage, and networking are bought from your preferred vendors or existing procurement channels. We can recommend a range, but the hardware spend is not revenue to us.
If you already have capable workstations, racks, or private cloud infrastructure, we can often start there and scale only when usage justifies it.
No. Sometimes a HIPAA-eligible cloud setup is more practical and cost-effective. We recommend on-prem when privacy, procurement, latency, or internal governance makes external AI usage too risky or too slow to approve.
Yes. Private speech-to-text and note drafting is one of the clearest use cases for healthcare teams that want productivity gains without moving patient conversations outside their environment.
No. We provide planning guidance and reference estimates, but the hardware is purchased directly from vendors by the client. Our commercial role is implementation and ongoing maintenance.
Yes. In many engagements, we work alongside internal infrastructure, security, and compliance stakeholders so the deployment fits your policies rather than bypassing them.
Next step
Bring the real problem: transcription, internal search, document processing, patient support, or something more specialized. We will help you scope the right architecture and rollout path.