Build Trustworthy AI

Technical AI Governance Solved

Fit Tikos to any model and comply with emerging regulations for transparency, explainability, contestability, fairness, accountability, robustness, accuracy

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Intro

Regulators have spoken

AI EU ACT
GDPR Art. 22
ISO/IEC 42001
NIST AI RMF
Sectoral Regs (FCA, MHRA, etc.)

Regulators around the world continue to refine their expectations of AI system owners, particularly in high-stakes and regulated sectors.

Their demands are beginning to impact corporate policies in security, risk, data, IT, and procurement and are surfacing in cyber insurance policies.

Whilst the details change with jurisdiction and industry a clear theme is emerging: AI systems and applications must be trustworthy, a necessary standard to satisfy users, compliance teams, auditors, and regulators.

Fair & Unbiased
Systems must be able to justify how decisions are made and identify and address potential biases in their training data or operation.
Explainable
Individual system outputs must be explainable to users and developers. Interpretation (LIME, SHAP) will not achieve the desired standard.
Transparent
Systems must be transparent and include sufficient information to enable users to understand the system’s capabilities and limitations.
Accountable
Systems must incorporate human oversight to interpret its operation, understand its outputs and override it when necessary.

What options do ML/AI Leaders have?

Downgrade to simpler models

Downgrade to simpler (more linear and transparent) but less effective models. OK if you can afford to take a performance hit.

Undertake new development

Develop new models that maintain performance and keep compliance happy. OK if you have budget and confident it’ll solve the problem.

Add more humans in the loop

Redesign observability and oversight with more process and support staff. OK if you have skilled resource available.
High risk sectors under scrutiny
Finance & Insurance
Healthcare
Transport
Energy
Telecoms
Utilities
Law & Justice
Pharmaceuticals
Defence & Security
Science & Research

Solved by adding Tikos to your pipelines

Tikos retrofits to any model, gathering insights on every decision output to comply with all emerging 'trustworthy AI' themed regulations.

Achieve compliance without the cost, hassle or disruption of new development, new hires or new roadmaps.

Retrofit ANN models
Integrates directly with deep learning models at the decision inference stage: feed-forward, recurrent, graph, LSTMs, auto-encoders.
Retrofit standard models
Integrates with standard statistical ML models: regressions, random forests, GBMs, SVMs, Bayesian.
Serves all stakeholders
Tikos outputs help engineers with model development, users to understand, and compliance teams with reporting to auditors and regulators.
Secure deployments
SaaS solution deployed securely into any private cloud or dedicated environment.

Get started today

Evaluate Tikos with a small-scale POC and then roll-out across your model registry.

Proof of Concept

£POA

Select one model/pipeline
Configure for engineers/users/compliance
1:1 support
Subscriptions from

£495/month

All models/pipelines
Configure for engineers/users/compliance
1:1 support
Features
Retrofit implementation

Implement to any existing model or pipeline

Included
Deploy securely in any environment

SaaS deployment in your client tenant and retain complete control

Included
API first

APIs, SDKs or full platform options

Included
Model agnostic

Standard ML or deep-learning models supported

Included
Proprietary technology

Leverages a decade of research (PhD) in AI reasoning and explainability

Included
Enterprise workloads

Proprietary distributed processing

Included
1:1 support

Dedicated support for engineers, executive and GRC teams

Included

Have a question or want more information?