Data Technology & AI Strategy
Stage 1 - Use Case Assessment
Objective is to assess the potential for AI and data technology applications generally. Deliverables at this stage include recommendations around capability gaps, data availability and organisational readiness to adopt AI tools.
Stage 2 - AI Foundations
The objective of Stage 2 is to identify needs driven use cases, build a pro-forma business case and the strategy blue print for AI in the organisation. The decision to commit to this stage depends on the outcome of Stage 1.
Stage 3 - Internal Engagement
Stage 3 is to engage internal stakeholders supported by the pro forma business case and ROI estimates
Stage 4 - Solution Design & Delivery
Stage 4 is the design, build and deliver stage of the application against the use case
Stage 5 - Ongoing Support
If required enable AI provides outsourced services managing the cloud environment and AI systems to ensure performance and uptime:
Data & AI Productivity Tools Review
There are so many new tools popping up in the market today, and its difficult to keep track of what they do and for what purpose. We conduct reviews of various data technology tools that may be appropriate to address a particular business need (use case) and provide recommendations.
In addition we will recommend situations where bespoke tooling may be most appropriate for particular business processes and pain points.
Data Modelling and Visualisations
This is the process of building out projection models to measure impact. Impact means demonstrating the impact of implementing data technology on key performance metrics of the business, whether they be economic metrics or non-economic such as social impact (patient outcomes, lives saved etc).
The purpose of these analytics and visualisations is to help persuade stakeholders in decision making, particularly around approvals with respect to investing, donating or securing government grants.
Tailored Productivity Tools
Where off the shelf tools are not quite right for the needs of the business to solve inefficiencies, or to maintain control and privacy over data for example, we design and implements tooling tailored to the business. This is particularly important in highly regulated industries (insurance, healthcare, superannuation etc).
In the era of AI Agents and the relative ease and low cost of building tailored solutions, the technology and cost barriers of building your own in-house productivity tools is now much lower making data and AI innovation accessible to all businesses.