Pre-approved EPIC6 pricing + AWS credits mean your first assessment or pilot can be largely funded. Ethical, compliant, public-sector-ready.
Includes pre-approved EPIC6 rates; 1.5% EPIC6 admin fee already priced in; equal pricing for all members.
.svg)
Procurement made simple. Funding made possible.
EPIC6 → PO → AWS Credits → Pilot in 6–8 weeks
Identify 3 high-impact use cases, compliance review, roadmap. AWS funding eligible up to $25K.
Architecture, data deep dive, PoC design. AWS funding eligible up to $40K.
Bedrock-based pilot with metrics. AWS PoC funding eligible up to $75K.
Multilingual constituent/student services with hand-off.
Forms/PDF automation using Textract + Bedrock.
Ground responses in your policies and records.
Secure experimentation environment.
Chatbot + Prompt Workshop + IDP for student records.
The AWS GenAI Assessment is a program designed to evaluate opportunities, align capabilities with your organization’s goals, and deliver a tailored plan for succesful, future-proof AI adoption.
Ready for the AI era? We’ll show you how to get there.
In the initial phase, we identify and prioritize high-impact Generative AI opportunities within your organization. Leveraging process mapping, competitive analysis, and technical deep dives, we develop a clear, actionable use case opportunity matrix aligned with your business objectives.
We assess your organization’s data landscape to ensure readiness for AI adoption and identify any potential gaps. We perform a comprehensive data inventory, evaluate data quality in terms of accuracy, completeness, consistency, and timeliness, and review data accessibility, integration capabilities, and formats.
All applicable regulatory requirements are assessed, along with your organization’s security and privacy controls. Existing technology infrastructure and integration points are evaluated, API capabilities and system interoperability are reviewed, and a risk assessment with corresponding mitigation strategies is conducted.
A comprehensive AI model assessment is conducted, with recommendations on the models best suited for the top use cases identified. Our evaluation considers performance and capabilities, cost efficiency, reliability, and consistency, delivering a detailed recommendation supported by evidence and analysis of total cost of ownership.
In this phase, we design the technical architecture and system integration approach for your AI initiative. We define implementation phases, timelines, and critical milestones, and identify the resources, time, and materials required for a proof-of-concept or production-ready deployment.
Expected benefits are quantified, including cost savings and revenue opportunities, with calculated return on investment across multiple scenarios. We develop a TCO model, including ongoing operational costs, success metrics and key performance indicators, and prepare an executive summary with strategic recommendations.
As a conclusion to the assessment, we provide guidance and documentation on the steps required for ethical AI implementation, addressing key principles including Fairness, Explainability, Security, Safety, and Governance.
Our delivery is SOC 2-aligned, WCAG-conscious, and embeds ethical AI governance (fairness, explainability, safety). We specialize in AWS Bedrock, SageMaker, Textract, and serverless architectures built for secure scale.
AlertCalifornia (CAL FIRE) — temporal AI improved smoke detection.
Metropolitan Water District of SoCal — on-call ops with strict SLAs, ADA & security focus.
Rightsline (IDP on AWS) — measurable cost/time savings with Textract + Bedrock.
-1-1.jpeg?width=1129&height=950&name=Untitled%20presentation%20(6)-1-1.jpeg "Untitled presentation (6)-1-1")
“They have been a very flexible partner in terms of scope and timeline and are absolutely critical to helping us navigate the AWS funding landscape. They bring a lot of domain knowledge, but are also very open to learning from our findings and expertise; it's definitely a team-oriented culture. We absolutely love working with Metal Toad!”
Here are five common mistakes to avoid when creating a GenAI strategy:
1. Skipping the Business Validation Phase
Jumping straight into development without validating the GenAI use case can lead to wasted resources.
2. Overengineering the Solution
Building complex AI features without a clear user need often leads to bloated, underused products.
3. Ignoring Infrastructure and Scalability Needs
Failing to account for model performance, latency, and cost optimization on AWS can lead to inefficient, unsustainable deployments.
4. Neglecting Data Privacy and Compliance
Ignoring data governance, model transparency, or compliance requirements like SOC 2, HIPAA, or GDPR can create legal and reputational risks.
5. Lack of a Cross-Functional Strategy
Treating GenAI as a standalone tech project instead of a cross-functional business initiative limits impact.
We leverage our AWS GenAI Competency to address common challenges in GenAI planning:
1. Business Validation with AWS PoC Funding
We help clients secure AWS Proof of Concept funding—up to 40% of projected annual spend —to test GenAI use cases.
2. Lean, Impact-Driven Development
Our team delivers focused MVPs using agile development and prompt engineering, enabling fast iteration.
3. Cloud-Native, Scalable Architecture
We design optimized architectures using Amazon Bedrock, SageMaker, and serverless frameworks to balance performance, scalability, and cost.
4. Built-In Security and Compliance
Security is integrated from day one. We ensure compliance with SOC 2, HIPAA, and GDPR, along with responsible AI practices to protect your data and brand.
5. Cross-Functional Strategic Alignment
Our engagements bring together engineering, design, product, and legal teams—ensuring your GenAI solution aligns with business goals and delivers measurable value.
Metal Toad achieves AWS GenAI Competency, enhancing our ability to deliver innovations and drive digital transformation for clients in multiple...
Metal Toad is now an Amazon QuickSight Service Delivery Partner, showcasing expertise in data visualization and business intelligence solutions.
AWS shifts focus from ML to generative AI with new certifications, reflecting evolving tech and market needs. Explore the implications for...
Maximize your GenAI potential with Metal Toad’s AWS GenAI Assessment — delivering scalable, high-value solutions that take your organization from...
Why do so few Small & Midsize Businesses (SMBs) use AI? How can they address the capabilities gap in order to stand up their own AI initiatives?
Extend your AWS Bedrock models with Knowledge Bases to enhance retrieval-augmented generation, leveraging large context windows and efficient data...
