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Our Competencies

GenAI Competencies

AI Governance

  1. AI Risk Management Framework

  2. LLM Evaluation/Reasoning

  3. Monitoring Dashboard of Key Metrics

  4. Comparative Study between LLMs

LLM (Large Language Models)

  1. Customized Enterprise LLM Workflows

  2. LLM Training and Enhancement

  3. MLMM (Multimodal Large Language Models)

Application Development

  1. Prompt Engineering

  2. Custom & Cost-Optimized Pipeline for Specialized NLP Tasks

  3. Enterprise RAG

  4. Virtual Assistants

AI/ML Competencies

Data Analysis

  1. Exploratory Data Analysis

  2. Building Dashboards

  3. Visualization Tools: Tableau, Power BI

Advanced Analytics

  1. Machine Learning

  2. Supervised / Unsupervised / Reinforcement Learning

  3. Regression / Classification

  4. Anomaly Detection

  5. AI Algorithms

Deep Learning Models

  1. Fully-connected, CNN, RNN

  2. LSTM, Transformer

  3. Encoder-Decoder, GAN, LLM

Deployment & Operations

  1. DevOps

  2. MLOps

  3. Optimized MLOps/AIOps

  4. Model Deployment

  5. No/Low Code Platforms

Responsible AI/Interpretable AI/ML

Data Competencies

Data Governance

  1. Data Quality Assessment & Evaluation

  2. Data Protection Compliance

  3. Data Protection Assessment & Evaluation

  4. Data Classification & Access Process

Data Source/Data Repository Architecting

  1. Relational Databases

    1. Postgres, MySQL, etc.

    2. MSSQL Server

    3. Oracle

  2. NoSQL Databases

    1. Document Database

    2. Graph Database

    3. Vector Database

    4. Time-Series Database

  3. Cloud vs On-Prem vs Hybrid

  4. Data Warehouse Technology

  5. Data Lake Technology

  6. Data Mesh Technology

  7. Cloud Big Data Platforms

  8. Cloud Migration

  9. Cloud Refactoring

Data Processing

  1. Workflow Orchestration

  2. Data Pipeline

  3. Batch/Stream Processing

  4. Big Data Processing Tools

Case Studies: Driving Success Across Industries

  • Responsible AI Documentation for a Smart Interview Platform

    DeepDive Labs collaborated with a smart interview platform to develop a Responsible AI framework, ensuring regulatory compliance and building client trust in highly regulated industries. This framework evaluates the platform's processes against the Fairness, Ethics, Accountability, and Transparency (FEAT) principles established by the Monetary Authority of Singapore, providing detailed documentation on data usage, scoring methodologies, and system limitations. By addressing concerns about algorithmic bias and ethical standards, the framework enhances the platform's credibility and facilitates smoother client onboarding.

    Read more here »

  • Cloud re-engineering to save costs

    DeepDive Labs assisted a smart interview platform in reducing their cloud expenses by 65% and enhancing processing speed by approximately 50%. The client initially relied on Azure Video Services to analyze candidate interview videos, which became cost-prohibitive after their Azure credits expired.

    DeepDive Labs conducted a thorough analysis of the system's usage patterns and proposed a cloud refactoring and migration strategy. This involved re-architecting modules to utilize in-house models and transitioning to AWS's speech-only services, which are more cost-effective and efficient.

    This case underscores the importance of continuous monitoring and optimization of cloud services to manage costs effectively.

    Read more here »