Data Enablement for Regulated Industries
Transparent, explainable AI for high-impact, low-risk environments.
Fluence delivers auditable, data-driven business transformation for regulated industries.
Our uniquely auditable Machine Learning framework empowers organizations in pharma,finance, automotive, and other regulated sectors to harness the power of Artificial Intelligence with confidence.
By fostering a perfect understanding of organizational data and its impact on performance, we enable our clients to maximize sales, optimize resources, and manage risk.
Through our comprehensive approach and tailored solutions, we are a trusted data partner
for regulated organizations worldwide, driving their continuous growth and success.
Technology and services that adapt seamlessly to your strategic imperatives.
Orientate organizational output around the maximization of core KPIs, such as sales targets and revenue trajectories. Concentrate resources around impact.
Automate the detection and management of risk. Guard against decision inconsistency. Harmonize the expertise of your team to ensure quality, repeatability and accountability.
“Fluence serves as our corporate memory, pooling the collective experience of our technical specialists to improve the quality, safety and consistency of future decisions. This programme of work allows us to ensure the highest level of value, efficiency and accountability for the taxpayer.”
Steve Davy – Head of Technical Standards
AI re-designed for clarity and impact
Regulated industries demand more than accuracy; understanding is crucial.
Fluence has developed a Machine Learning framework designed specifically to overcome the auditability challenges that prevent low-risk organizations from harnessing AI’s true potential.
Our ground-breaking suite of technologies unravels the prediction process, pinpointing the data and features that drive your commercial outcomes.
Our technologies also reveal the ‘why’ behind predictions, including circumstantial influences linked to bias and decision inconsistency, ensuring that models are trustworthy, unbiased and usable in ‘high-governance’ environments.
Barriers to implementation
- Inability to trust the model’s results.
- Inability to understand the ‘why’ behind decisions.
- Inability to understand the influences on the model.
- Inability to learn from the model.
- Inability to align model behaviour and staff behaviour.
- Inability to safeguard data usage.
- Inability to mitigate reputational risks.
Explainability with Fluence
- Understand precisely which features and characteristics led to every decision.
- Detailed breakdowns of model influences, allowing internal teams to monitor the data for reliability, risk and bias.
- Deep understanding of strengths and limitations of the models, allowing clients to ensure appropriate controls.
- Data is always yours.
- Models are always yours.
- Control is in your hands
Explainability embedded into every decision
- Measurable, backable decisions: Enabling leadership teams to alter tactics and reallocate resources.
- Enhanced reporting: Feed curated insights directly into intelligence reports.
- Risk mitigation: Auto-identify biases in current data, guard against biased models.
- Pattern detection: Surface hidden correlators between activity and (e.g. activity might work in one context, but not another).
- Source monitoring: Evaluate the reliability of your prior history. For example, decisions made by one expert may be more reliable indicator of future performance than another.
- Hyper-optimization & personalization: Receive detailed feedback on how to optimize actions right down to an individual level.
- Model feedback: Receive detailed justification for every insight and prediction in a manner that is accessible to non-technical staff
Analytics that work for you
Explore natural patterns in your data and how they align to your commercial outcomes.
Identify patterns of activity associated with specific commercial outcomes, or that are prone to elevated risk or reward.
Capture, standardize and harmonizethe views of multiple experts.
Users can impart their expertise onto documents, allowing Fluence to harness their knowledge, combine it with other experts, and monitor decision variance between experts.
Identify patterns of activity that are directly correlated to top-level company performance.
Connect your content and unstructured data to real-world performance metrics (e.g. sales volumes, financial performance, or safety logs) to surface valuable commercial optimizations.
Founded in 2016, Fluence is a British/Swiss deep-tech Al company, bringing together some of the finest engineers from Cambridge University and ETH Zurich. The team has decades of senior engineering experience at major Silicon Valley companies.
The team has developed a core technology capable of reverse engineering relationships between unstructured data and outcomes. It allows organizations to learn quickly from history and apply lessons dynamically to future activities.
Fluence’s unique advances in auditable Machine Learning allow teams to truly understand the relationship between activity and outcome. The team has extensive Silicon Valley experience and has succeeded in developing a genuinely auditable Machine Learning framework designed to adapt dynamically to the specific requirements of sophisticated global clients.