Direct answer
Google Cloud credits after AWS Activate can make sense, but only when there is a real Google Cloud reason. "We used AWS credits and want another bucket" is weak. "We have an AI, data, Firebase, BigQuery, migration, or customer-driven Google workload" is the case worth reviewing.
Partner route
Applying cold is often the weakest route. Partner review can package the case better.
The direct Google form checks program fit. A partner-led review asks the commercial question Google actually cares about: is this account worth supporting because of workload, projected spend, AI or data usage, migration, implementation need, customer timing, or provider growth?
No-cost initial review
A realistic route check should not cost the startup money. The partner is compensated by the provider or channel side when a qualified account moves forward. Paid implementation work is separate if it is not provider-funded.
Public form
Company age, website, AWS account, package rules, prior credits, Org ID.
Partner review
Run-rate, workload fit, migration plan, funded work, payment terms, retention case.
Cost to startup
The initial fit check should not cost money when there is a realistic provider opportunity.
Guardrail
No guaranteed credits, no fake Org ID, no partner shortcut without a real workload.
Best next step
New to Google credits?
Start with the main Google Cloud startup credits route.
AI-first startup?
Check the AI-specific credit path and workload signals.
Used AWS first?
Check when a Google route is real and when it is just credit shopping.
Ready to apply?
Prepare the evidence before using the direct form or partner route.
Direct route weak?
Compare credits, discounts, funded work, migration, and payment terms.
AI workload
Vertex AI, Gemini, model serving, agents, inference, evaluation, or data pipelines create a real Google Cloud reason.
Strong when AI is the product, not a word in the deck.
Data or Firebase fit
BigQuery, Firebase, analytics, customer reporting, or product data can make Google Cloud more than a credit reset.
Strong when the architecture actually changes.
Migration case
Moving from AWS to Google Cloud can be credible when there is a scoped migration, modernization, or customer requirement.
Weak when the only reason is the credit headline.
Post-AWS commercial route
If the workload should stay on AWS, the better ask may be discounts, terms, funded work, or post-credit review.
Strong when AWS usage is real and growing.
Published program context
AWS publicly describes Activate credits up to $100,000 for eligible startups and requires the right package path, including Activate Provider and Org ID logic for Portfolio. Google publicly describes startup cloud credits up to $200,000, or up to $350,000 for AI-first startups. Those are separate programs. The second route needs its own fit.
Sources: AWS Activate credits Google Cloud Startups Google for Startups Cloud Google Cloud AI startup program Google Cloud partners
The dugri rule
AWS Activate history can help only if it proves real usage. If the credits were consumed by production workloads and the next stage has a clear Google Cloud reason, the history is useful evidence. If the credits expired unused or the company just wants another free runway, the case is thin.
Do not ask Google to reward the fact that AWS credits ended. Ask whether Google Cloud is the right platform for the next workload, and whether the account is worth supporting through credits, discounts, funded implementation, migration support, or payment terms.
When the Google route is credible
Vertex AI or Gemini
A model, agent, inference, RAG, evaluation, or AI product workload that can run on Google Cloud.
BigQuery or analytics
A data warehouse, customer analytics, reporting, event pipeline, or BI modernization project.
Firebase or app platform
A mobile or web app workload where Firebase, hosting, auth, storage, or analytics changes the build plan.
Customer requirement
A buyer, enterprise customer, region, compliance, data, or integration reason that points to Google Cloud.
Migration or modernization
A scoped move from AWS, DigitalOcean, Azure, or another stack with implementation work attached.
Funding or growth trigger
A new round, grant, launch, or customer contract that makes the next 6-12 months of spend visible.
When it is probably credit shopping
Only AWS credits ran out
That is not a Google Cloud strategy. It is a cash problem.
No Google-specific workload
If AWS still fits technically, force-fitting Google Cloud can make the case weaker.
No usage proof
If AWS credits were mostly unused, they do not prove a bigger cloud opportunity.
Vendor-cost confusion
Google Cloud credits do not automatically cover third-party software. Review vendor and marketplace routes separately.
No implementation plan
A migration or AI/data pitch needs a project, not just a one-line intention.
Asking too late
A rushed application after AWS credits expire is weaker than a prepared commercial review.
AWS history vs Google Cloud case
Why partner review can beat dealing with Google alone
A founder applying alone usually has one lever: the form. A serious partner has a different job: qualify the account, pressure-test the workload, prepare the evidence, and route the case in a way that makes commercial sense. That does not mean guaranteed credits. It means the ask is no longer just a founder asking for free cloud.
Google says its partner network is built around certified experience and partner-delivered services. That is the public version of the moat. The practical version is simple: a partner that understands Google Cloud, migrations, AI/data projects, and startup account growth can often frame the opportunity better than a cold application.
Evidence to prepare
AWS credit history
Package used, amount granted, remaining balance or expiry, and whether the credits were consumed by real usage.
Gross AWS usage
Monthly run-rate before credits, top services, service mix, and the first full bill forecast.
Google Cloud workload
What will run on Google Cloud, why it belongs there, and expected usage over the next 3-6 months.
Trigger
Funding, customer contract, AI/data project, migration, launch, or expansion that creates timing.
Implementation need
Architecture, migration, security, data, AI, optimization, or partner-delivered work that makes support useful.
Commercial ask
Credits, discounts, payment terms, funded work, migration support, or a recommendation to stay on AWS.
What to check next
If the AWS path itself may still be stronger, read after AWS Activate credits. If you are new to the Google route, start with Google Cloud startup credits. If AI is the main reason to move, read Google Cloud AI startup credits. If you are ready to apply, use the Google Cloud startup application checklist.
If credits are not the strongest ask, compare partner-led commercial routes, startup cloud commercial options, and the cloud commercial route checker.
Bottom line
Google Cloud after AWS Activate is a good page only when the startup has a real second-cloud reason. If the reason is AI, data, migration, Firebase, BigQuery, customer demand, or new spend, partner review can package it. If the reason is just "AWS credits ended," do not dress it up.
