Intelligence Engineering

Analytics

Transform raw data into actionable insights to improve short-term decision-making and long-term strategic planning. Drive intelligence with a full range of analytics: descriptive, diagnostic, predictive, prescriptive, and generative.

Content Engineering

Some of the world’s largest and most innovative organizations count on us for model alignment. Tap into our proven human-in-the-loop processes to support deployment of LLMs and LLM-powered applications within your organization.

MLOps

Blending deep industry and technical experience, our team helps organizations establish and maintain clear processes for leveraging AI/ML solutions. We are platform agnostic and have a track record delivering multiple use cases.

Cybersecurity

GlobalLogic has a dedicated practice with experience and expertise in cybersecurity and cryptography. We harness these strengths as we deliver all Intelligence Engineering capabilities—including deploying security for AI and AI for security.

AI Governance

Whether engineering a data platform, preparing data for AI, or implementing GenAI applications, you need to ensure appropriate management, protection, and optimization of your information. GlobalLogic can help.

Knowledge Management

• Knowledge extraction from large sets of unstructured data
• Smart search based on intent detection, context, correlation, and recommendations
• Summarization and knowledge synthesis
• Proactive agentic knowledge curation

Content Generation

• Retrieval augmented generation for increased relevance
• Natural language editing for style and volume
• Visualizing data (tables, charts, graphs)
• Document layout, illustrations, graphic design
• Creative ideation and iterative refinement

Sensory Perception

• Ingestion and generation of audio, video, and sensor data
• Quality enhancement and normalization
• Segmentation and feature extraction
• Object recognition and classification
• Object tracking in recorded or real time inputs

Multimodal Human-Machine Interfaces (HMI)

• Text/speech/image recognition to extract information
• Text/speech/image generation to present information
• Integrating multiple input modalities into a unified knowledge model
• Sentiment analysis based on indirect visual and audio cues

Content Analysis

• Natural language processing for meaning, context, relevance
• Sentiment analysis for mood and intent
• Classification for themes and attributes
• Duplicate and overlapping content optimization
• Error detection and correction

Synthetic Data Creation

• Numerical data and human-readable content generation
• Applying transformations to existing data to enhance the variability
• Comparing synthetic and real-world data to ensure realism
• Anomaly generation to ensure coverage of rare cases