Frequently Asked Questions

AWS Activate and AWS partner funding programs serve different purposes and are accessed differently. Activate is a self-serve credit program for startups. You apply directly with AWS, no partner involved, and receive credits that offset your AWS service costs. Partner funding programs focus on PoCs, building production workloads, migrations, etc., and are accessed through a qualified AWS Partner and can cover both AWS service costs and the engineering labor to build or migrate your workload. Activate is the right starting point for early-stage companies looking to offset infrastructure burn. Partner funding is the right next step when your project involves assessing and implementing work that unlocks new capability or services on AWS.

AWS Activate is AWS's credit program for startups. It provides free AWS service credits to help early-stage companies get their products running on AWS without paying full infrastructure costs out of pocket. Activate is self-serve. You apply directly with AWS, no partner required. Credits are tiered based on your startup's stage and backing. Self-funded and bootstrapped companies can apply directly for the entry tier. Companies backed by a qualifying venture capital firm, accelerator, or incubator can access significantly more through the Portfolio tier. AI startups that have exhausted Portfolio credits may qualify for an invite-only track with higher availability. Activate covers AWS service costs only. It does not cover consulting, implementation labor, or partner fees. A partner can be involved from the start while Activate credits are running which means the credits reduce your AWS bill, and partner funding programs can cover the implementation work alongside them. The two are designed to complement each other, not to run in sequence.

MAP is a migration program. It funds the movement of existing workloads to AWS, not the development of new applications. A net-new AI project being built on AWS does not qualify for MAP regardless of which services it uses. That said, AI workloads can qualify for MAP when they involve migrating existing infrastructure — training pipelines, data environments, or inference workloads moving from on-premises or another cloud to AWS. For net-new AI builds, AWS has a separate mechanism: Proof of Concept (PoC) funding. The two programs are not mutually exclusive, and many AI-focused projects qualify for both depending on what is being built versus what is being moved.

MAP funding applies to companies migrating existing workloads from on-premises infrastructure or a competing cloud provider to AWS. The workloads must be moving to AWS and staying there. Net-new development, workloads already running on AWS, and workloads being retired do not qualify. Scope also matters: single-workload migrations are generally too small. Migrations with multiple production workloads moving to AWS are the more typical fit. MAP requires a qualified AWS partner, so customers cannot apply directly. Whether your specific project qualifies depends on factors AWS evaluates during scoping, not a checklist you can run in advance.

AWS MAP stands for Migration Acceleration Program. It is AWS's primary funding program for companies moving workloads from on-premises infrastructure or another cloud provider to AWS. The program is structured around three phases: Assess, Mobilize, and Migrate and Modernize. Funding is available at each stage with credits being applied directly to your AWS bill and partner cash funding the engineering work. You cannot access MAP funding without a qualified AWS partner involved. Tech 42 is an AWS Advanced Tier Services Partner and helps customers determine eligibility, scope migrations, and submit MAP funding requests.

Estimating AWS Bedrock costs starts with three inputs: request volume, average input tokens, and average output tokens. Use the free CountTokens API to get exact token counts before writing production code. It accepts your real prompts and returns model-specific counts at no charge. The bigger risk is what the token formula misses: Knowledge Base infrastructure, CloudWatch logging, and agent token amplification together often add 20 to 35 percent to the inference bill. Our workload-based Bedrock Cost Calculator builds a baseline estimate from the numbers you already know, like users, documents, or images per month, without requiring you to work backward from requests per minute.

Amazon Bedrock AgentCore is the AWS platform businesses use to build and run AI agents in production. It went generally available in October 2025. AgentCore handles the infrastructure around your AI model: where the agent runs, how it connects to your tools, and how you govern what it is allowed to do. It is modular, serverless, and consumption-based, which makes it cost-effective for low and moderate usage. At high volume, or for teams with complex infrastructure requirements, a custom build may be worth evaluating. Whether AgentCore is the right fit depends on your use case, your expected usage volume, and how much infrastructure your team wants to manage.

AWS partner tiers (Select, Advanced, Premier) reflect increasing levels of certified staff, completed engagements, and customer satisfaction data. The most important structural difference is that Premier partners must hold at least three AWS Competencies, each earned through audited production case studies. But tier alone does not guarantee expertise in your specific workload. For targeted initiatives, a focused Advanced partner with relevant competencies may be a stronger choice than a Premier partner without them.

AWS organizes its consulting partners into three tiers — Select, Advanced, and Premier — based on verified certifications, completed customer engagements, and annual AWS oversight. The tier is a meaningful signal, not a marketing badge. This page explains what Advanced Tier actually requires, why it matters when you're hiring, and how AWS funding programs can reduce what you pay for implementation. It also covers the questions worth asking any partner before you sign.

Tech 42 leverages the full AWS AI/ML stack, prioritizing serverless and high-performance computing to balance cost with scale. Our core toolkit revolves around Amazon Bedrock for Generative AI, SageMaker for custom model training, and ECS/EKS for containerized deployment. Beyond core infrastructure, we specialize in purpose-built AI services like Textract and Bedrock Data Automation (BDA) for document intelligence and AgentCore for agentic workflows. While we are an AWS Advanced Tier Partner, we remain technology-agnostic, integrating Open Source tools (like LangGraph) where they offer superior flexibility.

Tech 42 Consulting is an AWS Advanced Tier Partner specializing in the design, build, and scaling of AI/ML applications. We function as a fractional AI engineering team for funded startups and high-growth enterprises, offering end-to-end services from AI strategy and roadmapping to infrastructure migration and production-grade deployment. Our core technical competencies include Generative AI (GenAI), Retrieval-Augmented Generation (RAG), Intelligent Document Processing, DevOps and cloud infrastructure optimization, and agentic workflows on AWS.