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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
Own the model, own the margin with purpose-built medical AI

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.
💸 Cut your clinic’s AI spend

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.
  1. Set encounters
  2. view SaaS cost climb
  3. 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)
  • Transcript + attachments (~8 000 tokens)
Live counters:
  • SaaS cost £X
  • LogiNet cost £Y
You save £ Z / month

How self‒hosted medical AI delivers ROI in just four weeks

Pick where it lives

Day 0 your infra, your rules
  • Choose on-prem, private cloud (Azure/Google), or hybrid
  • Fixed-fee SoW e-signed in two clicks
  • Kickoff call booked within 24 hours

Get your clinical chat assistant live

Week 1 running in your own environment
  • Open-source LLMs tuned to your specialties
  • containers deployed, guard-rails tested, HIPAA/GDPR audit logging on
  • EHR and dictation feeds connected (FHIR/HL7), notes and summaries ready to query

Bank the savings and protect PHI

Week 4 results you can bill on
  • Token spend down 60–80 % versus rented AI
  • Documentation time cut 30–50 % per visit; faster follow-ups and fewer callbacks
  • You own every model, embedding and log; PHI stays in your UK/EU tenant with predictable per-note economics

Self‒hosted AI in action: Real client wins

Our AI succes stories
Self‒service agent live in eight weeks
  • Went from blank page to live AI prototype in under two months
  • Blended a custom‒trained LLM with secure data pipes and a lean UI
  • Shipped a self‒hosted service bot now streamlining consulting workflows and slashing token spend
Mocxy.ai
David ODonnel
Founder, Mocxy.ai | AI fueled CX Design agency
"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!

Cut manual grind, gain AI speed

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
• Manual logging, scattered audit trails, DPIA overhead
• 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.
Balint & Laci working

Access to a pool of IT & AI experts

Get direct support from our professionals whenever you need extra hands.

Multilingual

expertise

We speak fluent English & work seamlessly across cultures, making collaboration smooth.

Proven success in remote delivery

We’ve delivered complex AI projects remotely: seamlessly, across teams and time zones.

No more abandoned AI projects

We stay post-launch, refining models so your assistant keeps paying off.

Faster time-to-value

Go from kick-off to production in four weeks, clinics see savings in the first month.

60–70 % lower token spend

Model routing and trimmed context turn volatile AI bills into a predictable line item.

AI that works, not just excites

Automates clinical note drafting, cuts documentation time, frees clinicians for patient care.

Data never leaves your walls

All data stays in your UK or EU cloud, fully HIPAA- and GDPR-aligned.

Fixed-cost, on-premise build

One capped fee, containers in your tenant: no surprise bills or data drift.

Access to a pool of IT & AI experts

Get direct support from our professionals whenever you need extra hands.

Multilingual

expertise

We speak fluent English & work seamlessly across cultures, making collaboration smooth.

Proven success in remote delivery

We’ve delivered complex AI projects remotely: seamlessly, across teams and time zones.

No more abandoned AI projects

We stay post-launch, refining models so your assistant keeps paying off.

Faster time-to-value

Go from kick-off to production in four weeks, clinics see savings in the first month.

60–70 % lower token spend

Model routing and trimmed context turn volatile AI bills into a predictable line item.

AI that works, not just excites

Automates clinical note drafting, cuts documentation time, frees clinicians for patient care.

Data never leaves your walls

All data stays in your UK or EU cloud, fully HIPAA- and GDPR-aligned.

Fixed-cost, on-premise build

One capped fee, containers in your tenant: no surprise bills or data drift.

Tools and technologies that power your AI success

From open-source models to custom workflows, here’s what drives real-world AI medical tech

Backend core

Python 3.11+ – orchestration, pipelines, FastAPI – REST & OpenAPI docs, SQL DB – MariaDB / PostgreSQL (+ time-series ext.), Redis – cache, sessions, Celery – background tasks / training jobs
Backend core

Model-workflow & deployment tools

TensorFlow Extended (TFX), PyTorch, ONNX & ONNX Runtime, JAX / Flax, CUDA / cuDNN, NVIDIA TensorRT, Triton Inference Server, Hugging Face Transformers / Diffusers / PEFT, MLflow, PaddlePaddle
Model-workflow & deployment tools

Commercial foundation-model APIs

OpenAI GPT family, Google Gemini, Anthropic Claude, Microsoft Phi (Phi 4), Alibaba Qwen, Cohere Command-R, Amazon Titan (Bedrock)
Commercial foundation-model APIs

Open-source LLMs

Llama 3 (8B / 70B), Mixtral 8×22B, TinyLlama, Falcon 180B / 40B, Phi-3-mini (MIT), Qwen-14B / 72B, RWKV, Vicuna / Alpaca / Orca, RedPajama, BLOOM, GPT-J, GPT-NeoX, GPT-Neo
Open-source LLMs

Text-to-speech engines

ElevenLabs Voice AI, Microsoft Neural TTS, Google Cloud TTS, Amazon Polly, OpenAI TTS, Murf AI, PlayHT
Text-to-speech engines

Speech-to-text engines

OpenAI Whisper, Deepgram, Google Speech-to-Text, AssemblyAI, Amazon Transcribe, Microsoft Speech
Speech-to-text engines

Computer-vision APIs / libraries

GPT-4o Vision, Azure Vision Studio, Google Vertex Vision, AWS Rekognition, Roboflow, OpenCV
Computer-vision APIs / libraries

Image-generation models / services

DALL·E, Midjourney, Stable Diffusion, Runway (video)
Image-generation models / services

Agentic & workflow frameworks

LangChain, LangGraph, Haystack, Agno, LlamaIndex, AutoGen, CrewAI, Griptape, MetaGPT, ExaTools
Agentic & workflow frameworks

Vector databases / stores

Milvus (Zilliz), Pinecone, Weaviate, Qdrant, Chroma, pgvector, Redis Vector
Vector databases / stores

Embedding model families

OpenAI text-embedding-3, Cohere embed-v3, Google Gecko, Sentence-Transformers
Embedding model families

AI-powered search & retrieval tools

Perplexity, Exa.ai
AI-powered search & retrieval tools

Optimization engine

NumPy, SciPy, Pandas, OR-Tools (CP-SAT, VRP, MIP)
Optimization engine

Machine-learning stackBackend core

scikit-learn, LightGBM, XGBoost, TensorFlow / Keras, SHAP
Machine-learning stackBackend core

Backend core

Python 3.11+ – orchestration, pipelines, FastAPI – REST & OpenAPI docs, SQL DB – MariaDB / PostgreSQL (+ time-series ext.), Redis – cache, sessions, Celery – background tasks / training jobs
Backend core

Model-workflow & deployment tools

TensorFlow Extended (TFX), PyTorch, ONNX & ONNX Runtime, JAX / Flax, CUDA / cuDNN, NVIDIA TensorRT, Triton Inference Server, Hugging Face Transformers / Diffusers / PEFT, MLflow, PaddlePaddle
Model-workflow & deployment tools

Commercial foundation-model APIs

OpenAI GPT family, Google Gemini, Anthropic Claude, Microsoft Phi (Phi 4), Alibaba Qwen, Cohere Command-R, Amazon Titan (Bedrock)
Commercial foundation-model APIs

Open-source LLMs

Llama 3 (8B / 70B), Mixtral 8×22B, TinyLlama, Falcon 180B / 40B, Phi-3-mini (MIT), Qwen-14B / 72B, RWKV, Vicuna / Alpaca / Orca, RedPajama, BLOOM, GPT-J, GPT-NeoX, GPT-Neo
Open-source LLMs

Text-to-speech engines

ElevenLabs Voice AI, Microsoft Neural TTS, Google Cloud TTS, Amazon Polly, OpenAI TTS, Murf AI, PlayHT
Text-to-speech engines

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.
💸 AI ROI calculator

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
Clinical AI cost-cutting playbook

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Fresh thinking from LogiNet

AI resource centre: watch, learn, implement

From pilot to pay‒off: turning AI experiments into real ROI (2025 edition)
What’s inside the video?
  • Why chasing an “AI strategy” is a distraction, focus on profit leaks first.
  • Where to start: back-office workflows vs. client-facing experience.
  • Concrete ROI wins in support and sales (transferable to legal ops).
  • The truth behind the hype: 80 % of great AI is disciplined software engineering.
  • Live demo: a self-hosted voice agent resolving real customer calls, no SaaS lock-in, full control.

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.
John Radford
Client Services Director UK

…or simply book a 30‒minute AI cost audit on Calendly