Artificial Intelligence
Transform Challenges into
Opportunities
Analytica’s Artificial Intelligence (AI) experts help our federal clients safely operate at the forefront of AI innovation. We use best-in-class tools and technologies that unlock AI for our customers, delivering descriptive, predictive, and prescriptive recommendations. Our end-to-end solutions integrate into our customers’ existing IT infrastructure. Whether integrating local AI methods or partnering with cloud providers, we provide targeted solutions to our customers without sacrificing on safety, interpretability, or guardrails.
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Advantages of Artificial Intelligence
Analytica works with government customers to transform their operations through AI and Machine Learning (ML). These efforts result in
- Reducing manual effort with tedious processes related to unstructured data.
- Improving the speed of decision-making based on ML/AI algorithms.
- Providing end-users with their entire corpus of reference documents and policies at their fingertips to inform LLM responses to user queries.
- Personalizing infrastructure with appropriate choices with AI agents and underlying RAG architecture.
AI Expertise
With our innovative approaches, we help our clients to achieve their business goals:
- Generative AI Solutions
- Intelligent Document Processing
- Natural Language Processing
- Explainable AI
AI Innovation Roadmap
- Current AI Capabilities:
- Implement enterprise-ready LLMs for document analysis and insights generation
- Advanced predictive models with explainable AI at the heart of everything we do
- NLP-Enhanced Data Processing: Automated text analysis and sentiment extraction from unstructured data
- Near-Term Innovations
- Explainable AI Framework: Enhanced transparency to help clients understand model decisions and build trust
- Edge AI Deployment: Moving select analytics capabilities to edge devices for efficient computing and deployment
- Our Continuous Innovation Process
- Regular evaluation of emerging AI research with academic partners
- Bi-weekly and monthly innovation sprints focused on client challenges
- Internal AI innovation hub for testing and developing cutting-edge techniques
Problem ID
- ID customer challenges
- Translated into well-defined problems with measureable outcomes
- Evaluate what AI brings to the table
Scope ID
- Establish focused scope for POC
- Define clear, measureable success criteria
- Align on timelines with stakeholders
Data Assessment
- Evaluate data availability, quality
- ID potential biases
- Create data prep plan
- Address privacy and security concerns early and repeatedly
Technology Assessment
- Choose appropriate AI techniques based on the problem
- Consider the use of pre-trained models
- Evaluate tradeoffs of COTS vs custom development
- Select tech as a balance between innovation and practical implementation
Rapid Prototyping
- Start with simple models
- Use Agile dev
- Demonstrate core functionality
- Document technical choices and trade-offs
Validation
- Test with real-world data
- Evaluate performance beyond technical metrics
- Test for fairness, ethics, and potential biases
Stakeholder Feedback
- Employ HCD for customer-facing deployments
- Focus on highest business value
- Collect feedback from various perspectives
Iteration & Refinement
- Improve the POC using customer feedback
- Address edge cases and performance challenges
- Document lessons learned
Value Assessment
- Quantify business impact
- Develop plan for production implementation
- ID resources needed for next steps
Documentation
- Document entire process
- Create reproducible development environments
- Prepare training materials
Relevant Insights
Large Language Models Disrupt the Way We Work, But Not How You May Think
The internet is flooded with articles about large language models like ChatGPT, their potential, and […]
Enhancing DHS Generative AI Deployments with Open-Source Tools
The Department of Homeland Security (DHS) has a history of leading the way in integrating […]
Artificial Intelligence / Machine Learning for Regulatory Enforcement
Analytica is supporting the development of complex artificial intelligence and machine learning model development for the Securities and Exchange Commission (SEC) to combat insider trading and financial fraud. Our work applying artificial intelligence / machine learning for regulatory enforcement provides the SEC with the ability to reduce costs for regulatory enforcement while providing more accurate, actionable intelligence for enforcement.
