Sold by: eSparkBiz
eSparkBiz AWS Advanced Tier Partner architects provide the strategic architecture and technical leadership to take AI systems from concept through production deployment on AWS.
Overview
Most AI projects don't fail in the model. They fail in the gap between a working prototype and a production system that IT can actually support. eSparkBiz's AI Solution Architects close that gap, bringing the architecture, strategy, and technical leadership your AI initiatives need to run reliably in production, not just advice from the sidelines.
About eSparkBiz
eSparkBiz is an AWS Advanced Tier Partner established in 2010 with 15+ years of experience delivering tailored solutions. Our team holds AWS Solutions Architect and AWS Cloud Practitioner certifications. We maintain compliance certifications including SOC 2, ISO 27001:2022, CMMI Level 3, ISO 42001:2023, and ISO 27018:2019, ensuring the firm accessing your infrastructure meets the same standards we design into your architecture.
Architecture Focus Areas
- Data pipeline design on AWS: Architects map how data moves from source systems (Amazon S3, Amazon Kinesis, AWS Glue) into models hosted on Amazon SageMaker or Amazon Bedrock, addressing latency and quality issues before they reach production.
- Model integration architecture: Decisions on hosting via Amazon EKS or AWS Lambda, auto-scaling, and API Gateway design connect AI outputs to the applications your teams actually use.
- Security and governance design: Access controls via AWS IAM, audit logging through AWS CloudTrail, and data handling aligned to SOC 2 and ISO 27001 frameworks get built into the architecture from day one.
- Strategic cost and performance leadership: Every architectural decision comes with documented reasoning and AWS cost modeling, so technical choices survive budget review and compliance audits.
From Strategy to Scale
Phase 1: Discovery (1-2 weeks)
Architects assess your current AWS infrastructure and AI readiness, applying strategic judgment to identify where technical leadership will matter most. Your team provides access to existing systems and a technical counterpart for interviews.
- Deliverable: AI Architecture Readiness Scorecard with prioritized recommendations
- Prerequisite: Active AWS environment with identified AI use case
Phase 2: Design (2-4 weeks)
A documented AI architecture blueprint translates strategy into a buildable technical plan, with architecture decision records (ADRs) explaining every tradeoff and the leadership judgment behind it.
- Deliverable: Architecture Blueprint Document, ADRs, and implementation roadmap
- Buyer responsibility: Engineering lead available for weekly design reviews
Phase 3: Scale (Ongoing as needed)
Technical leadership continues as usage, data volume, and model complexity grow, ensuring the architecture holds up under real production strain. Includes handoff documentation for your engineering team.
- Deliverable: Implementation runbook, scaling playbook, and knowledge transfer session
Example Engagement
A financial services firm needed strategic architecture for a real-time fraud-scoring pipeline ingesting millions of daily events. eSparkBiz architects designed an end-to-end system using Amazon Kinesis for streaming ingestion, AWS Glue for data preparation, Amazon SageMaker for model hosting, and Amazon API Gateway for low-latency scoring responses, with full audit logging via CloudTrail to meet regulatory requirements.
Scope and Prerequisites
- In scope: Architecture design, strategic planning, documentation, integration patterns, security design, cost modeling, and implementation guidance on AWS.
- Out of scope: Model training and development, ongoing MLOps operations, and production infrastructure management.
- Prerequisites: Active AWS account, at least one identified AI use case, and an internal engineering team to receive the architecture handoff.
Get Started
Schedule a 30-minute AI readiness discovery call to determine fit and scope your engagement.
Highlights
- eSparkBiz is an AWS Advanced Tier Partner (est. 2010) with 15+ years of experience and certifications including AWS Solutions Architect, SOC 2, ISO 27001, and CMMI Level 3. Our architects bring strategic technical leadership to production-ready AI systems on AWS services including Amazon SageMaker, Bedrock, Kinesis, and EKS, closing the gap between proof of concept and enterprise-scale deployment.
- Every architecture decision is documented in Architecture Decision Records (ADRs) with tradeoffs, cost implications, and compliance alignment explained. Engineering leaders receive artifacts backed by real technical leadership they can use to defend infrastructure choices during budget reviews, security audits, and regulatory examinations, not just verbal recommendations.
- Engagements follow a structured Discovery (1-2 weeks), Design (2-4 weeks), and Scale methodology, with strategic direction and named deliverables at each milestone: an AI Readiness Scorecard, Architecture Blueprint, implementation roadmap, and scaling playbook. Scope boundaries and prerequisites are defined upfront so your team knows exactly what to expect and provide.
Details
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Resources
Support
Vendor support
Engagement Support
eSparkBiz provides structured, milestone-driven technical leadership throughout the AI Solution Architect engagement.
During Active Engagement:
- Architecture reviews occur at defined project milestones, validating design decisions and strategic direction against implementation constraints before costly rework begins.
- Weekly check-ins with your assigned architect during Design and Scale phases.
- Email response within 24 business hours during active engagement periods.
Scoping and Pre-Engagement:
- Schedule a 30-minute AI readiness discovery call to assess fit and define scope.
- No commitment required for initial consultation.
Post-Engagement Support:
- Knowledge transfer session included at engagement close.
- 30-day post-delivery window for clarification questions on delivered artifacts.
Buyer Responsibilities:
- Provide access to relevant AWS environments and system documentation.
- Designate a technical counterpart (engineering lead or DevOps engineer) for design reviews.
- Make stakeholders available for Discovery phase interviews.
Escalation: If issues arise between milestones, email your assigned architect directly. Unresolved concerns are escalated to the engagement manager within 48 hours.
Contact Channels:
- Email: sales@esparkinfo.com
- Visit us: