Opportunity assessment and solution design
Explore requirements and possible improvements, compare technical approaches, and test feasibility before committing to implementation.
Welcome to bitknowledge
AI engineering, integration and implementation.
Bitknowledge helps UK organisations explore, develop and implement practical applications of artificial intelligence, from identifying opportunities and evaluating solutions to integrating AI with existing systems and building the infrastructure needed to support them.
Finding practical applications for AI
Not every problem requires artificial intelligence, and not every AI application requires new infrastructure. Bitknowledge begins by understanding the problem, the existing processes and the systems already in use.
From there, we can evaluate whether AI offers a worthwhile improvement, explore the available options and test promising approaches before committing to implementation. Solutions may involve hosted AI services, locally deployed models, conventional software or a combination of technologies.
Linux and GPU environments
Set up Linux hosts, GPU drivers, NVIDIA/CUDA, storage and the supporting services needed to run AI workloads.
Model deployment and inference
Configure local model runtimes and inference services, with access controls and testing against the intended workload.
Commercial AI and hybrid integration
Connect hosted model APIs and cloud services to existing applications and local systems, with attention to data handling and ongoing costs.
Technical implementation
Carry out agreed project work, including networking, authentication, monitoring, testing and documentation.
Support and handover
Help with troubleshooting and upgrades, and explain how the system works so your team can look after it. Support responsibilities are agreed for each project.
The infrastructure around the model matters
For local and open-weight models, this can mean Linux and GPU systems, model storage, runtimes and inference services. For commercial AI services, it can mean integrating hosted model APIs, managing credentials and usage limits, and keeping costs under control.
Both need careful attention to authentication, networking and data handling: who can use the system, where information goes, and how it connects to the rest of the organisation.
Resilience matters too. Monitoring, recovery arrangements and sensible handling of service failures help turn an initial experiment into something people can use day to day.
Open systems, practical engineering
Open-source software can make a system easier to inspect, maintain and support. Access to the code and configuration helps with diagnosing problems, understanding dependencies and passing skills on to the people who will run it.
Bitknowledge favours open standards, interoperability and systems that can be understood and maintained. Open-source technologies are used where appropriate, alongside commercial services when they offer practical advantages. The aim is to build solutions that remain useful, supportable and adaptable as technology develops. Clear documentation and practical handover matter in either case.
Tom Jackson is an engineer at bitknowledge. Read his note about bitknowledge or find out more about the engineering approach and exploratory work.
Discuss a project
Tell Tom what you are exploring or where you need a hand. An initial idea, a question about existing systems, or a specific technical problem is a useful place to start.
hello@bitknowledge.com