Join our customers
Own the model, own the margin with purpose‒built legal AI
Practical AI tools for law firms to support legal professionals, streamline workflows and reduce costs
Research, diligence and client service—redefined
- AI legal research tool on demand
- AI due diligence tools for fast deals
Draft, review, and automate documents faster
- AI contract analysis in seconds
- AI for legal document review
- AI document automation for lawyers
- Legal document drafting AI assistant
Automate and monitor legal operations across the firm
- AI for legal case management
- Contract review automation 24/7
- Legal workflow automation that scales
- AI compliance monitoring made easy
Ready to cut costs and take control?
If a fixed-fee, private legal AI assistant sounds like exactly what you need, let’s talk.
💸 Cut your law firm’s AI spend
Calculate the savings your practice could bank with our legal AI solutions
See your token burn in real time
Type in your monthly document load and see, in pounds and pence, what GPT usage is really costing the firm, plus how much you could keep if everything ran on‒prem.
Monthly cost comparison
£0
£25
£50
£75
You Save
£60
per month
Annual Savings
£720
How self‒hosted legal 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 legal chat assistant live
Week 1 — running in your own environment
- Open-source LLMs fine-tuned on your matters
- Containers deployed, guard-rails tested
- DMS, email and case files indexed, ready to query
Bank the savings and keep control
Week 4 — results you can bill on
- Token spend down 60–70 % versus SaaS tools
- Contract review time cut by ~30 % on average
- You own every model, log and cost line—no shocks later
Self‒hosted AI in action: Real client wins
Our AI succes stories
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 how a self-hosted or private-cloud legal AI assistant slashes review time, spend and risk.
Critical metrics for AI-driven legal work
Cost per matter:
Document review time:
Data residency:
Responsiveness:
Audit and privilege:
Scaling to peaks:
Partner visibility:
Onboarding time:
Prompt control:
Vendor risk:
Before AI (manual or SaaS wrapper)
• Rising vendor licences and billable-hour leakage
• 6–8 hours per 1 000 pages, heavy paralegal input
• Contract data copied to external SaaS datacentres
• Overnight turnaround for large bundles
• Manual logging, scattered email trail
• Hire temps or pay SaaS overage
• Unclear ROI, hard to link cost to matter
• Weeks of vendor negotiation and data-export hoops
• Black-box prompts, no control over context windows
• Price hikes and feature removals outside your control
After LogiNet
self-hosted assistant
• Predictable fixed fee, 60–70% lower token spend
• 2–3 hours, automated clause matching and AI due-diligence tools
• All embeddings and vectors stay in your UK tenant
• Near-real-time answers while counsel is on the call
• Tamper-proof prompt and citation log, exportable on demand
• Spin up extra on-prem containers with no per-token penalty
• Live dashboard shows pounds, hours saved and accuracy per matter
• Containers deployed in days, no data leaves premises
• Full visibility and tuning of every prompt and retrieval step
• Model-agnostic design lets you swap vendors 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.
Tools and technologies that power your AI success
From open-source models to custom workflows, here’s what drives real-world AI legal 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
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
Commercial foundation-model APIs
OpenAI GPT family, Google Gemini, Anthropic Claude, Microsoft Phi (Phi 4), Alibaba Qwen, Cohere Command-R,
Amazon Titan (Bedrock)
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
Text-to-speech engines
ElevenLabs Voice AI,
Microsoft Neural TTS, Google Cloud TTS,
Amazon Polly, OpenAI TTS,
Murf AI, PlayHT
Speech-to-text engines
OpenAI Whisper, Deepgram, Google Speech-to-Text, AssemblyAI, Amazon Transcribe, Microsoft Speech
Computer-vision APIs / libraries
GPT-4o Vision, Azure Vision Studio,
Google Vertex Vision, AWS Rekognition,
Roboflow, OpenCV
Image-generation models / services
DALL·E, Midjourney,
Stable Diffusion,
Runway (video)
Agentic & workflow frameworks
LangChain, LangGraph, Haystack, Agno, LlamaIndex, AutoGen, CrewAI, Griptape, MetaGPT, ExaTools
Vector databases / stores
Milvus (Zilliz), Pinecone, Weaviate,
Qdrant, Chroma, pgvector,
Redis Vector
Embedding model families
OpenAI text-embedding-3,
Cohere embed-v3, Google Gecko,
Sentence-Transformers
AI-powered search & retrieval tools
Perplexity,
Exa.ai
Optimization engine
NumPy, SciPy,
Pandas, OR-Tools (CP-SAT, VRP, MIP)
Machine-learning stackBackend core
scikit-learn, LightGBM, XGBoost, TensorFlow / Keras, SHAP
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
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
Commercial foundation-model APIs
OpenAI GPT family, Google Gemini, Anthropic Claude, Microsoft Phi (Phi 4), Alibaba Qwen, Cohere Command-R,
Amazon Titan (Bedrock)
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
Text-to-speech engines
ElevenLabs Voice AI,
Microsoft Neural TTS, Google Cloud TTS,
Amazon Polly, OpenAI TTS,
Murf AI, PlayHT
Common partner questions & clear, candid answers
Cost & ROI clarity
We bill by the hour, will a fixed‑fee model really lift matter profitability?
What if OpenAI or Anthropic raise prices
overnight?
We already pay for a SaaS legal-AI tool; why isn’t that good enough? Why build your own legal AI chatbot?
If we leave the SaaS vendor, do we lose the vendor’s knowledge base and support ecosystem?
Client confidentiality, data sovereignty & regulation
We need airtight compliance.
Can AI still help?
Will any client matter data ever leave our UK or EU data centres?
Does a self‑hosted assistant keep us inside SRA guidance without extra paperwork?
Who owns the embeddings and knowledge base if we part ways with LogiNet?
Accuracy, control & risk mitigation
If the agent hallucinates, who carries the liability: you or us?
How do we stop juniors blindly trusting an automated answer?
Can we veto responses that exceed a risk threshold?
Implementation, integration & upkeep
How long from signature to first production chat?
Who watches token burn and latency once live, your team or ours?
What internal resources do we need?
Done exploring? Let’s start building.
You’ve got the answers. Now let’s build the artificial intelligence for lawyers your firm actually needs.
💡 The AI implementation reality check
Real costs. ROI ranges. Readiness. Spelled out.
Get a no-nonsense guide that helps you answer three things fast:
- Costs: clear bands for tools, integration, training, support.
- Returns: ROI ranges by use case, from service to finance.
- Readiness: one check: real problem, usable data, budget, buy-in.
Download now!
Drop in your work email and we’ll send you a 25-answer Q&A guide covering: cost breakdowns, expected payback, and a simple readiness test you can run this week.
By signing up you agree to receive LogiNet marketing communications. View our Privacy Policy for more info.
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 will confirm a time, benchmark your current AI spend, and outline a self-hosted roadmap that cuts costs while keeping every document inside your own infrastructure.
John Radford
Client Services Director UK
Current AI tools used
Select one or more options
…or simply book a 30‒minute AI cost audit on Calendly
Providing end‒to‒end web and mobile development services to our customers since 2008.