Own the model, own the margin with purpose‒built clinical AI
Practical AI & machine learning solutions for private clinics and healthcare providers that streamlines healthcare administration, improves private doctors’ workflows, and cuts costs.
Clinical documentation
AI for clinical decision support to surface risks and next-best actions
AI-assisted diagnosis for doctors using multimodal data and guidelines
AI for electronic health records to search, summarise and reconcile notes
Predictive analytics for private clinics to flag at-risk patients and no-shows
AI for clinical research to extract cohorts and build reproducible datasets
Operations & administration at scale
AI workflow automation for clinics to streamline intake, billing and referrals
AI appointment booking system with reminders and triage questions
AI scheduling for medical practices to balance capacity and demand
AI for patient data management with audit logs and retention controls
AI for healthcare quality improvement with real-time indicators and alerts
Patient access, triage & follow-up
AI medical chatbot for clinics for secure intake, FAQs and symptom checks
AI tools for private healthcare & AI tools for private doctors at the point of care
AI diagnostics for clinics to pre-screen images and structured data
AI solutions for small clinics that deploy in days, not quarters
Artificial intelligence for healthcare providers that you can own and extend
Ready to cut costs and take control?
If a fixed-fee, private AI solution for private clinics sounds like exactly what you need, let’s talk.
Calculate the savings your practice could bank with our medical AI solutions
// CUSTOM CODE CALCULATOR WILL BE HERE //
How much are your tokens burning this month?
Set patient encounters and average note size to see, in pounds and pence, what GPT usage is really costing your clinic — and how much you keep with a self-hosted stack.
Set encounters
view SaaS cost climb
See the LogiNet price cap drop
Encounters this month:
slider 0–5k; tick stops: 100, 500, 1k, 2.5k, 5k
Average note size:
Short SOAP / follow-up (~750 tokens)
Standard encounter / multi-problem (~2 500 tokens)
"The team at LogiNet International went above and beyond at every possible instance."
LogiNet International developed an LLM wrapper for GPT for a design agency. The team built a customer-facing portal and designed the UI and UX for the platform.
They team went above and beyond to meet the client's needs and identify additional requirements. Their proactive approach and outstanding final product impressed the client.
I will definitely return to this company for more work, and they will be my first recommendation when asked!
See the before and after with AI solutions for private clinics, covering cost per encounter, documentation time, PHI residency, auditability and scale.
Metrics that move the needle for your clinic
Cost per encounter:
Documentation time per encounter:
PHI residency and data control:
Responsiveness (note turnaround):
Auditability and compliance:
Scaling during peaks:
Clinical and finance visibility:
Onboarding time:
Prompt control and safety:
Vendor risk:
Before AI (manual or SaaS wrapper)
• Variable, per-token bills that rise with usage
• 10–15 minutes per visit, heavy clinician after-hours work
• Notes and embeddings copied to external SaaS datacentres
• End-of-day batching, delays to follow-ups and coding
• Overtime or SaaS overage during flu season/surge clinics
• Unclear ROI, hard to link AI spend to throughput and revenue
• Weeks of vendor negotiation and data-export hoops
• Black-box prompts, no control over context windows or retrieval
• Price hikes, feature removals, lock-in to a single model
After LogiNet
self-hosted assistant
• Predictable fixed fee, 60–80% lower token spend
• 4–7 min with AI note drafting and AI for electronic health records summarisation
• All PHI, embeddings and logs stay in your UK/EU tenant (HIPAA/GDPR aligned)
• Near-real-time notes and summaries at point of care
• Tamper-proof query and citation logs, exportable on demand for audits
• Spin up extra on-prem containers with no per-token penalty
• Live dashboard maps £ and minutes saved per encounter, by specialty
• Containers deployed in days, connectors for FHIR/HL7 configured quickly
• Full visibility and tuning of prompts, RAG sources and model routing
• Model-agnostic design lets you swap providers without rewrites
Built by experts who’ve been doing AI before it was a buzzword
At LogiNet, we’ve been delivering real-world AI solutions since long before GenAI became a trend. From LLM-based assistants to privacy-first automation, we’ve built AI tools that run inside critical systems—fast, safe, and tailored. Our AI chat agents don’t just answer questions. They understand your business.
ElevenLabs Voice AI,
Microsoft Neural TTS, Google Cloud TTS,
Amazon Polly, OpenAI TTS,
Murf AI, PlayHT
Healthcare AI questions, answered plainly
Cost & ROI clarity
We bill by the appointment. Will a fixed-fee model really lift margin per encounter?
Yes. We move you from variable, per-token fees to a fixed monthly cost with clear per-encounter economics. With RAG and model routing, clinics typically cut token spend 60–80%, so documentation, triage and AI for healthcare administration stop eroding margin.
What if OpenAI or Anthropic raise prices overnight?
Your assistant is self-hosted or private-cloud and model-agnostic. If a foundation model’s tariff jumps, we can re-route to lower-cost options (including open-source) without rebuilding. That keeps AI solutions for private clinics predictable and protects your budget.
We already pay for a SaaS medical scribe. Why isn’t that good enough? Why build your own AI medical chatbot for clinics?
SaaS tools are convenient, but you still pay per token and can’t tune the prompt stack. With your own AI medical chatbot for clinics, you control context windows, routing and data retention—cutting costs and keeping PHI in your tenant. It’s real machine learning for healthcare you can govern and extend.
Will we need to budget for new GPUs or long cloud reservations?
Not necessarily. We size the stack to your load and can run on your existing cloud. Many clients start on a modest private-cloud footprint; others add GPUs later. Either way, the goal is a fixed, forecastable cost line rather than open-ended usage bills.
Client confidentiality, data sovereignty & regulation
We need airtight compliance.
Can AI still help?
Yes. The full stack runs in your UK/EU tenant, with HIPAA/GDPR-aligned logging, access controls and audit trails. Use cases like AI for electronic health records search, AI for clinical decision support and AI workflow automation for clinics are implemented with data-minimisation and role-based access.
Will any patient data ever leave our UK or EU data centres?
No. PHI, embeddings and logs stay in your environment. We don’t transmit records to public endpoints—critical for artificial intelligence for healthcare providers operating under ICO and GDPR.
Does a self-hosted assistant reduce paperwork for audits and DPIAs?
We provide architecture diagrams, logging schemas and DPIA/BAA templates to support your compliance posture. Keeping data residency local simplifies reviews and AI for healthcare quality improvement reporting.
Who owns the embeddings and knowledge base if we part ways with LogiNet?
You do. All embeddings, prompts, indexes and orchestration code are yours, so your team—or any partner—can keep building. This matters for long-term AI in private medical practices and AI solutions for small clinics.
Accuracy, control & risk mitigation
If the agent hallucinates, who carries the liability: you or us?
You remain data controller; we’re your processor. We reduce risk with retrieval-first answers, citations, versioned sources and confidence scores. Clinicians stay in the loop, which is best practice for AI-assisted diagnosis for doctors and AI diagnostics for clinics.
How do we stop clinicians blindly trusting an automated answer?
Every response can show sources, timestamps and a confidence label. You can require human sign-off for sensitive workflows (e.g., coding/billing) and restrict the assistant to read-only EHR contexts for safety.
Can we veto responses that exceed a risk threshold?
Yes. Set blocklists, specialty-specific guard-rails and escalation rules. High-risk prompts can be routed to a supervisor queue—useful for predictive analytics for private clinics and AI for clinical research workflows.
Can we veto responses that exceed a risk threshold?
We pin retrieval to approved, date-versioned sources, enforce recency filters, and surface the guideline date in answers. Your governance group can update sources without a code deploy.
Implementation, integration & upkeep
How long from signature to first production note?
Most clinics see a live assistant in four weeks: week 1 infra and guards; week 2 EHR connectors (FHIR/HL7); week 3 tuning for note types; week 4 go-live with dashboards.
Who watches token burn and latency once live, your team or ours?
Both. You get a cost/latency per-encounter dashboard; we run proactive alerts and weekly reviews. This keeps AI tools for private healthcare performant and the cost line flat.
What internal resources do we need?
A clinical champion, one technical contact (≈½ day/week), and a staging EHR dataset. Optional add-ons (e.g., AI appointment booking system, AI scheduling for medical practices) can come later.
Can we expand beyond scribing to admin and triage?
Yes. The same stack powers AI tools for private doctors across intake, AI for patient data management, billing/coding, and front-door triage with an AI medical chatbot for clinics—all governed in your tenant.
Done exploring? Let’s start building.
You’ve got the answers. Now let’s build the artificial intelligence tools your healthcare team actually needs.
Need the numbers on paper? Grab the cost‒cutting playbook for clinics
Build the budget case for clinical AI
Put hard numbers behind documentation and throughput gains
Show predictable per-note economics your clinical leadership will trust
Download now!
Drop in your work email and we’ll send you a ready-to-use ROI calculator: designed to help medical teams justify budget, track impact, and make smarter AI decisions.
Ready to shrink your AI bill? Book your 30‒minute AI cost audit
Share a few details and we’ll confirm a time, benchmark your current AI spend, and outline a self-hosted or private-cloud roadmap that cuts costs while keeping PHI inside your own environment.