Harness the Power of Data and AI to Drive Growth

With growing data and rapid AI advancements, businesses need smarter ways to succeed. Our custom data and AI services help you collect quality data and turn it into actionable insights.

Value driven Data and AI services

Our approach ensures your data and AI services are technically robust, aligned with your business goals, and
focused on delivering real value

Data-driven decision making

We dive into your business’s current way of working and competitive landscape to create a data strategy that aligns with your business goals and sets a path for seamless AI integration.

Customer experience

Our predictive analytics and custom AI solutions are tailored to forecast market changes, automate processes, and revolutionize customer experiences.

Risk management solutions

From automating the mundane to deploying cognitive computing applications, we streamline your operations, leaving error and inefficiency behind.

Data governance and compliance

In a world where data privacy is paramount, we champion robust data governance and ironclad compliance with GDPR, CCPA, and beyond.

Data infrastructure and management

We design your data infrastructure for the heavy lifting, ensuring your data warehousing and big data management are ready for large volumes of data.

Training, change management, and adoption

With comprehensive training and change management, we help your team prepare for new AI solutions — increasing adoption and utilization.

We work with all leading tech stacks

Our approach ensures that your data and AI Services are technically sound, closely aligned with
your business goals, and capable of delivering tangible value.

Data Visualization

SQL Server AWS Glue Azure Data Factory Kafka Airflow Spark NiFi Oracle Oracle

An agile approach to data analytics excellence

At ScriptStory, we transform your data challenges into business accomplishments, guiding you
from initial discovery to full-scale data empowerment.

Plan Design Build Analyze & Act Change Management
Inputs
  • Business objectives and strategy
  • Stakeholder requirements and expectations
  • Current data landscape and capabilities assessment
  • Budget, timeline, and resource planning
  • Regulatory and compliance needs
  • Roadmap and project scope from the planning phase
  • Identified data sources and formats
  • Requirements for data storage, security, and processing
  • User experience and reporting needs
  • Data governance and compliance guidelines
  • Detailed designs for data architecture, models, and ETL pipelines
  • Technology stack (e.g., databases, analytics tools, visualization tools)
  • Data sources and integration requirements
  • Testing plans and performance benchmarks
  • Clean, structured data from the build phase
  • Analytical models and algorithms
  • Business rules and KPIs
  • User-defined metrics and benchmarks
  • Analytical insights and recommendations from the previous phase
  • Stakeholder feedback and business goals
  • New business processes and strategic decisions
  • Feedback from stakeholders and users
  • Training requirements for new tools and processes
  • Impact assessment on existing workflows and teams
Outputs
  • Data analytics roadmap
  • Defined use cases and KPIs
  • Project scope and goals
  • Stakeholder alignment and approval
  • High-level architecture and technology selection
  • Regulatory and compliance needs
  • Data architecture design (e.g., data lake, warehouse, pipeline)
  • Data model design and schema definitions
  • ETL (Extract, Transform, Load) design specifications
  • Analytical models and visualizations design plan
  • Defined roles and responsibilities for implementation
  • Implemented data pipeline (ETL or ELT processes)
  • Data warehouse or data lake setup
  • Data models and structures populated with live data
  • Initial dashboards and reports developed
  • Initial quality and performance testing results
  • Analytical insights (descriptive, diagnostic, predictive, prescriptive)
  • Data visualizations, dashboards, and reports
  • Actionable recommendations based on analysis
  • Identification of trends, patterns, and anomalies
  • Feedback for further iterations or refinements
  • Data-driven decision-making and actions
  • Stakeholder engagement and communication plan
  • Training programs for users and teams
  • Adoption of new tools, processes, and workflows
  • Monitoring of success metrics and post-implementation reviews
  • Continuous improvement and adaptation framework

Benefits of work with Script Story

Intensive users of customer analytics are 23 times more likely to outperform their competitors
in new-customer acquisition than non-intensive users.*

Data-driven decision making

We dive into your business’s current way of working and competitive landscape to create a data strategy that aligns with your business goals and sets a path for seamless AI integration.

Customer experience

Our predictive analytics and custom AI solutions are tailored to forecast market changes, automate processes, and revolutionize customer experiences.

Risk management solutions

From automating the mundane to deploying cognitive computing applications, we streamline your operations, leaving error and inefficiency behind.

Commonly Asked Questions

Generative AI refers to algorithms that can create new content, including text, images, and music, by learning patterns from existing data.

Common applications include content creation (writing, art, design), chatbots, virtual assistants, and even drug discovery.

LeewayHertz offers custom generative AI development services, including solutions for industries such as finance, healthcare, and more.