Photo by Markus Spiske on Unsplash
Our small ML team at Altitude Shift does short term engagements creating AI proof of concepts and finding AI opportunities.
WHAT we do
We are a small AI consulting and development consultancy.
We help clients discover AI opportunities.
(see here for some examples)
HOW we do it
We do quick, small experiments and proof of concepts to validate the use of AI in your organisation.
The proof of concepts are generally:
- A useable web demo with user interface
- Data management systems
- Machine learning and visualisations
Our aim is to create business value, discover risks or find and explore opportunities.
WHY – Finding value with AI
When engaging with AI, it’s a very expensive and risky proposition to go in no holds barred. In some respects AI engagements have a greater aspect of R&D than many innovative projects.
It’s asking a lot of an organisation’s leaders to hire a team of data scientists, data engineers, machine learning engineers, and a famous chief scientist to lead them. Then the organisation needs to engage that new team to build the data and machine learning infrastructure, integrate the new team with the business and the business culture, all without severely harming the business along that journey.
Traditional digital transformation is already a risky business, AI transformation can require much more a strategic commitment to resources, training and even cultural change, but we don’t want to make that commitment without proving that AI is useful to an organisation.
It’s challenging for many organisations to commit to being innovative, but getting them to invest millions without any guarantee of success is a hard ask.
As with any human endeavour, one way to approach AI is with small experiments, with exploration and limited pilots. Once we have proved the business value of an AI experiment, we can build momentum with further incremental investment with further experiments, until we validate having an AI strategy, prove value creation and build capability. Then we can make larger strategic decisions which might mean building infrastructure, engaging large scale partners or even buying startups to drive further AI success.
Our Philosophy – 3 Pillars : Discovery, Augmenting Differentiation and Augmenting Expertise
First pillar : Discovery.
We enable organisations to take those small steps towards adopting AI, and we orient our efforts around proving business desirability, feasibility and viability with AI and ML experiments and POCs. Our experience in technology startups means that we are first and foremost business and people focused, technology is seen as a means to an end, not as an ivory tower to be subservient to.
Second Pillar: Augmenting Differentiation
Companies spend a lot of time building competitive differentiation. It is our view that AI efforts should be focused on trying to increase competitiveness, to take catalyse an organisation’s raison de vivre, to make it better. Creating pioneering innovation wont happen with copying best practice, it will happen with innovation.
Third Pillar: Augmenting Expertise
Two common ways to split engagement with AI is to automate business processes or to augment people’s expertise. Our goals are to augment to expertise of an organisations staff. We see wins in productivity, often via reducing staff numbers seems as short term and unsustainable. Our aim is for emerging technologies to make us better, not redundant.
In any startup one needs to create new stand our products and services via a discovery and prototyping projects. We think that this is a viable way for many organisations to approach AI adoption, and if you think so too, please don’t hesitate to get in contact.
Our Process at high level
- Discovery:
- Explore Needs
- Explore Data & Data onboarding
- Proof of concepts / Prototypes
- Explore interfaces
- Build machines
- Visualise