Deliver working ai solutions

deliver Customised, fully integrated AI and ML capabilities across your organisation

Delivering AI in Production

turn your ai idea into a production reality

build, integrate, deploy without having to increase your headcount

learn from our team as we collaborate

turning ai ideas into working capabilities is challenging

  • Your team is busy!

  • You’ve never run an AI project before - how is it done?

  • You can’t find the right skillset quick enough on the market.

  • You need to get your application built ASAP and can’t delay to hire a full team.

  • You’re ready to build, but not sure that you’ll need AI skills into the long term.

  • You need to focus on your core competencies, not waste time learning a new specialism.

Our deliver package will help you take your ai ideas from paper to production

We’ll help you cover the full process of building out AI applications: from design to implementation, testing and deployment.

Our methodology, honed over years of building AI and Data Science applications, is specifically designed to avoid the common pitfalls with these projects. By integrating the contrasting processes of software engineering and AI / ML, we enable coordinated effort that successfully delivers.

We deliver working software with integrated AI capabilities, deployed and running – ready to provide value to your business as quickly as possible.

How does it work?

Our method combines several concurrent processes to synchronise AI and application development, ensuring all elements of building an AI solution combine to an end solution ready to use:

1. The Tech Spec

Before we start, we’ll work with you to describe the project and its goals in detail. This includes:

  • Defining terminology

  • Describing use cases and workflows

  • Identifying risks and constraints

  • Agreeing how the AI / ML models will be evaluated

  • Mocking up the user interfaces

  • Deciding how the success of the deployed project will be measured - whether by usage, time saved or other metrics - and how the solution will facilitate these measurements.

The discipline of taking extensive time to write a through tech spec ensures that we properly understand your goals and have properly thought through all of the implications and permutations of your ideas.

2a. AI Experimentation

We’ll develop a plan to develop the core of the AI or ML capabilities. Typically, this will involve a series of rapid “experiments” evaluated over carefully curated datasets.

By building up in complexity we gain confidence over the solution, identify edge cases and develop mechanisms for handling them correctly.

2b. Minimum deployable solution

Concurrently with the AI Experimentation, we’ll develop the “minimum deployable solution” (MDS). A common source of overruns in AI projects is the lengthy path to take a solution from a local enviornment to its production context.

The MDS mitigates this risk by attempting an early deployment of a skeleton solution, generating learnings which can be applied early in the project lifecycle to ensure smooth deployment at the end.

3A. The quest for efficiency

When the quality of the AI or ML component is sufficient we turn our attention to efficiency. We’ll deploy the full range of techniques and tricks to make the AI / ML components meet your cost and latency requirements.

3B. FEATURE IteratION

While the AI team focuses on efficiency, the engineering team is steadily adding features and complexity to the end application. At this stage, some of the AI / ML components are mocked and some may be real.

By developing, testing and evaluating in rapid cycles we are able to steer development on-the-fly, adapting with agility to changes in requirements or to challenges that arise.

4. Final integration

As the AI / ML and engineering work nears conclusion, we integrate the two. Our initial design will have left both components loosely coupled, enabling you and your team to switch prompts or models or upgrade the software without encountering difficult dependencies.

5. Deployment, user Testing and Go-Live

Following integration and deployment, we run a testing period so you can verify and validate with your teams and customers to ensure the project meets their needs.

Once live, the solution will measure its effectiveness, giving you the data to demonstrate the ROI of your investment and the success of your solution.

what do i get?

Deliver covers everything you need for your AI application:

  • A fully integrated and deployed application.

  • All source code, including Infrastructure as Code for deployment.

  • All design and architecture documents.

  • Testing results and outcomes.

  • End-user guides and documentation

  • Early life support.

Where and how to deploy is often a challenge for companies. We have experience in and can support any deployment architecture including:

  • Fully hosted by us – we can offer an ongoing managed solution, so you focus on your core competencies and leave the hosting to us.

  • Deployed to company cloud (e.g. Azure, AWS, GCP) – fully comply with the needs of your IT team: we can deploy into any cloud environment managed under your organization.

  • Hand over to your IT – we can hand a packaged application over to your IT team and support them in deploying it. 

 FAQs

  • It is. Getting high quality AI models integrated needs far more experimentation and handling of unknowns than building software.

    We know it is possible to run an AI build with a tightly defined process, and we handle the ambiguity, unknowns and different tasks required so you can see progress and have confidence in the outcome.

  • Yes. We’re familiar with a number of public cloud offerings and can support the full range of deployment options.

    Whether your IT team would prefer to deploy the application themselves, you’d prefer a fully managed solution or something in between, we can support it.

  • No. There’s no need to have completed a phase of work with us before starting a Deliver project.

    We find that we have the most success with customers when some discovery work has already been completed.

    However, we can also build a lightweight discovery process into a delivery project if you have a fully formed idea ready to go.

  • Absolutely. We offer tailored support services that ensure smooth operation and minimal downtime.

    With expert troubleshooting and fast response times, you can trust us to keep your application running.

why does it work?

It’s all based around a trial, focusing the work on measurable business outcomes from inception.

The sequence of rapid experiments builds confidence, generates important learnings and explores AI’s capability and reliability early.

By collaborating closely with business SMEs throughout the project we can use their detailed knowledge to iteratively improve capabilities as we go.