Our Commitment to Data Security
At Kahoa, your data security is our top priority. We adhere to strict confidentiality protocols, ensuring that access to your audit information is limited to three designated Kahoa agents and any individuals you identify in writing. Our security measures don't stop there; we employ two-factor authentication validated by your team and house all audit data on encrypted servers.
Upon completing the Audit and Certification process, all your data is handed back to you, and any remnants on our servers are promptly deleted. Our commitment to your data's confidentiality is not just a promise, but a contractual obligation that survives the termination of our agreement. Rest assured, we go to great lengths to keep your confidential and proprietary information secure.
AI Preliminary Assessment
We assess the AI system and learn what it does. We not only want to understand your AI system’s intended goals, but how it achieves those goals. Our team identifies key stakeholders and seeks to understand their perspectives.
- Key Business Stakeholders
- Existing and Planned AI Projects
- Engineering and Data Science Teams
- Infrastructure Deployments
AI Strategy Review
We want to make sure everyone is on the same page when it comes to your organization’s AI strategy. Our team reviews your objectives and strategies to validate they are well-defined, measurable, realistic, and in line with your company’s overall goals.
- Goal Alignment
- ROI Analysis
- Client-Centric Approach
AI Data Audit
A thorough analysis of your data. We examine the quality and ethical sourcing of the data that feeds your AI models, ensuring the models have been built on a solid foundation. Our goal is to eradicate poor data quality that will compromise the overall model’s performance.
AI Algorithm Evaluation
Our algorithm evaluation dives deep into AI model architecture, real-time inferences, and data handling. We meticulously audit each step, from feature extraction to MLOps, ensuring your AI algorithms are efficient and ethical.
- Model Inferences
- Data Manipulation
- Data Cleaniness
- Missing Value Handling
- Exploratory Data Analysis
AI Performance Assessment
Our AI performance assessment revolves around assessing real-time inference latency and scalability. We determine whether your model fulfills user interaction speed requirements while maintaining accuracy. We ensure the system is fortified against prevalent AI threats and vulnerabilities.
- Resource Efficiency
AI Ethics Review
Our team assesses the ethical implications of your AI system, ensuring that it complies with all legal requirements and specifications. We ensure that necessary safety measures are taken to protect user privacy and avoid discrimination or bias.
- Advers Impact Analysis
- AI Model Discriminative Bias
- AI Model Vulnerability & Distributional Drift
- Cost-Effectiveness of Model Inference
AI Risk Assessment
AI is a powerful technological tool gaining ground at a rapid pace. There is a great need for organizations to manage the associated risks to prevent adverse effects. We ensure that your AI system is trustworthy and aligned with necessary human goals and values.
- Data Handling and Privacy
- Algorithm Bias
- Compliance and Legal Risks
- Security Risks
- Transparency and Explainability
- Operational Risks
AI Infrastructure Review
We verify you have the right technology to accomplish your goals through a deep analysis of your organization's infrastructure. We ensure that revenue is not being lost on unnecessary hardware and that there is room for up-scaling if needed.
- Hardware and Cloud Infrastructure
- DevOps and CI/CD Practices
- Data Preprocessing and Feature Engineering
- Monitoring and Logging
- Data Ingestion and Integrations
- Data Storage and Security
AI Maintenance and Monitoring
The longevity and reliability of your AI systems rely on proper maintenance and monitoring. From data backups and disaster recovery to real-time performance tracking, we verify your AI system is safeguarded against potential pitfalls while keeping your AI models performing at their peak.
- Data and Feature-Store Backup
- Model Monitoring and Perfomance Tracking
- Disaster Recovery
- Review Model Retraining and Update Procedures
AI Stakeholder Analysis
As part of the stakeholder analysis, we know who is in charge of each aspect of the AI system and determine if these individuals are actually capable of accomplishing their given tasks. This means examining each stakeholder's goals, the resources/skills they have available, and the potential impact of their decisions on the AI system.
- Talent Assessment
- Stakeholder Buy-in
- Resource Allocation
- Action Plan
Testimonials: What Our Clients Are Saying
Without their help, we may have gone out of business. We saw a 1,000% increase over the maximum capacity of our legacy systems, over 48,000 orders per day, and an average of 75 million page views and 2.3 million unique users each month in 2017.
Asif is a brilliant computer scientist, a physicist, an original thinker, an erudite scholar, and an artist who can sculpt new algorithms, and paint new solutions, veritably a Leonardo da Vinci of our times, and a passionate educator with deep insight into AI/ML/DL/Data-Science/Big-Data topics.
When it comes to Big-data and machine learning, I would simply say he (Asif) knows A-Z in that. No matter what the domain is, he has machine-learning-based solutions for the problems involved. Working with him for years, I have realized how his predictions on the machine learning revolution in big data have come true.
We’ve done development in the past..the SolutionMap is a higher level way of defining a comprehensive approach to getting the success that you want.
It was not just about software…it was all about what is this going to do in your company, how are the people in your organization with your partners and with your other stakeholders going to interact with this piece of software and what are their expectations of it…it also helped us on the backside thinking about our business processes…it was really illuminating to me.
From the design through to the development detail, they listened, understood, and carefully tested before release, often pushing our initial ideas to a better outcome.