AI Platforms We Use
The models, frameworks, and infrastructure we build on.
Start Your ProjectWe are not locked to one vendor. We choose models and frameworks per use case, balancing capability, latency, cost, and data residency, across OpenAI, Anthropic, AWS Bedrock, and open models.
- Platform and model selection
- Vendor-neutral architecture
- Cost / latency benchmarking
- Data residency handling
- Fallback and redundancy
- Migration between providers
You are deciding what to build your AI on and do not want to bet the product on a single vendor’s pricing, availability, or roadmap, or you are already locked into one and feeling the cost of it. Models and prices change fast, and the right choice differs by use case and by data-residency rules. If AI is becoming core to your product, a vendor-neutral architecture keeps you free to pick the best option per task and switch as the landscape shifts.
How We Approach It
Match platform to use case
We select models and frameworks per task across OpenAI, Anthropic, Bedrock, Gemini, and open models, rather than forcing one vendor on everything.
Benchmark the trade-offs
Capability, latency, and cost measured on your actual workloads, so choices are backed by data instead of marketing.
Respect data residency
Architecture that keeps data where compliance requires, including running inside your own AWS account where needed.
Build in resilience
A vendor-neutral design with fallbacks across providers and a migration path, so you are never stuck if one changes price or availability.
The Difference It Makes
Vendor-Neutral
Right tool per task, no lock-in.
Benchmarked
Choices backed by real measurements.
Compliant
Data residency and privacy respected.
Resilient
Fallbacks across providers.
Technologies We Use
Common Questions
Are we locked into one provider?
How do you pick a model?
Related Services
Ready to Scale Your Infrastructure?
Book a free 30-minute consultation. No sales pitch, just engineering advice for your project.