Satalia AI Discovery Workshop - 90-Day Action Plan in 4 Hours

From AI Ambiguity to Action in Half a Day

The Satalia AI Discovery Workshop is a focused, high-impact session designed for leaders who need clarity and momentum before committing to full AI implementation. In just four hours, our senior AI consultants work with your team to identify the right opportunities, quantify potential value, and define practical next steps.

Workshop Approach:

This is not a passive presentation—it's a facilitated working session built around your specific business challenges. We combine 15+ years of AI implementation experience with proven discovery frameworks to quickly align stakeholders, frame problems clearly, and create executable plans.

What We Cover:

Problem Framing & Success Criteria Define clear problem statements with measurable success criteria aligned to business outcomes. Identify target KPIs, constraints, and decision criteria for evaluating AI opportunities.

Opportunity Sizing & Value Drivers Quantify potential business impact across efficiency gains, cost reduction, revenue growth, and risk mitigation. Map value drivers to specific use cases and prioritize based on ROI potential.

Current-State Assessment High-level mapping across jobs-to-be-done (JTBD), processes, data landscape, and existing systems. Identify gaps, dependencies, and integration requirements without requiring extensive documentation.

Risk & Constraint Analysis Explicitly document technical, organizational, regulatory, and data risks. Address feasibility concerns, resource constraints, and change management requirements upfront.

Quick Wins Identification Shortlist immediate opportunities that can deliver value within 90 days. Separate tactical wins from strategic initiatives requiring longer investment. Deliverables (Within 2 Business Days):

1-2 Page Opportunity Brief Concise executive summary with problem framing, opportunity sizing, recommended approach, and resource requirements. Shareable format designed for sponsor alignment and budget approval.

Prioritized Backlog Visual matrix mapping AI opportunities by effort vs. impact. Sequenced roadmap with clear next steps, dependencies, and decision gates.

PoC Proposal Practical, actionable plan for proof-of-concept including scope, timeline (typically 8-12 weeks), success metrics, data requirements, and estimated AWS consumption.

Workshop Format:

Duration: 4 hours (can be split into two 2-hour sessions if preferred) Delivery: Remote via video conference or on-site at your location Facilitation: Senior AI consultant with domain expertise Participants: 2-4 key stakeholders (leadership, business owners, technical leads) Cost: Complimentary (£0 / $0) Following the workshop, organizations typically proceed to:

8-12 week proof-of-concept on AWS infrastructure Full-scale AI implementation with managed services Ongoing AI advisory and optimization support Security & Confidentiality:

All discussions operate under your security standards. We work within your IP environment and provide NDAs as required. Workshop materials are tailored to your industry context and remain confidential.

The Satalia AI Discovery Workshop helps organizations identify and architect AI solutions using the comprehensive AWS AI/ML stack. During the workshop, we assess opportunities across these AWS services and design proof-of-concept implementations tailored to your use cases: AI & Machine Learning

Amazon Bedrock – Foundation models for generative AI applications, including text generation, summarization, and conversational interfaces Amazon SageMaker – Custom machine learning model development, training, and deployment for specialized use cases Amazon Rekognition – Computer vision capabilities for image and video analysis Amazon Textract – Intelligent document processing and data extraction Amazon Comprehend – Natural language processing for sentiment analysis, entity recognition, and text classification

Data & Analytics

Amazon S3 – Scalable data lake storage for training data, model artifacts, and output datasets AWS Glue – ETL pipelines for data preparation and feature engineering Amazon Athena – SQL-based data exploration and analysis Amazon QuickSight – Dashboard creation for AI insights visualization

Compute & Orchestration

AWS Lambda – Serverless inference endpoints and event-driven AI workflows AWS Step Functions – Orchestration of multi-step ML pipelines and workflows Amazon ECS/EKS – Container-based model serving for production deployments

Governance & Security

AWS IAM – Fine-grained access control for AI resources and data Amazon CloudWatch – Monitoring, logging, and alerting for AI workloads