Don't lock in the wrong model.

AWS Bedrock offers dozens of foundation models, and that's before you consider self-hosted andfine-tuned options. Tech 42 evaluates each against your real use cases on cost, quality, and speed,so you can make your decision based on data, not gut feel or the latest chatter on X.

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AI Model overwhelm

Why choosing a model feels impossible.

You need to know how the options stack up for your specific use case, not some generic benchmark.

01
Benchmarks don't tell the whole story
The wrong model can yield poor accuracy, slow responsetimes, and wasted budget.
02
Cost-saving models sacrifice performance
Self-hosted models promise cost savings but introduce performance unknowns.
03
Validation takes time your team doesn't have
Rigorous, unbiased evaluation is its own project you don't have the time an expertise to tackle.
know before you build

How custom model evaluation works

Get a comprehensive evaluation report and production-ready recommendation from an AI/ML Architect for a fixed fee scope in 3 to 6 weeks.

Phase 1
Discovery
We align on your business goals and define what "good"looks like for your use case.
-> You get a custom, clear evaluation framework
Phase 2
Quality Testing
We benchmark each model against your real prompts using G-Eval and task-specific metrics.
-> You get accuracy, relevance, & quality scores
Phase 3
Performance Testing
We measure latency, throughput, and cost at production scale with your application.
-> You get real-life speed & cost comparisons
Phase 4
Recommendation
We analyze which model fits your needs and budget and deliver clarity on your use case.
-> You get a data-driven model decision

Models we evaluate:

AMAZON BEDROCK
Foundation models from top labs
Claude (Anthropic), Titan (Amazon), Llama (Meta), Command (Cohere), Jurassic (AI21), and more
Self-Hosted
Open-source models on AWS infrastructure
SageMaker, EKS, and EC2 infrastructure enables scalable architectures with open-source models
Custom / Fine-Tuned
Your proprietary, speacialized models
Proprietary models require equally specialized evaluation (model training is not included)
RESULTS That Speak for Themselves

Pick a model that scales with your business

Tech 42 evaluates models to ensure that you can meet performance goals and drive profitability.

“
Working with Tech 42 has been a great experience. The team helped us successfully transition from our Hugging Face setup to an AWS SageMaker environment, enabling us to fine-tune and deploy our models within our own infrastructure. This not only gave us better control but also set us up for future scalability.

The Tech 42 team went above and beyond expectations - delivering a training script and process that streamlined our workflows, and providing excellent support whenever we had questions. Communication was clear and responsive, and we always felt supported throughout the project.

Overall, we are very satisfied with the results and the expertise the team brought to the table. We look forward to continuing our partnership with Tech 42 in future phases."
Murat Alpman
Chief Innovation Officer, HealthCorum
See more testimonials ->

Pick your AI model with confidence.

We scope every model evaluation at a fixed fee so you avoid hourly overages. Plus some projects qualify for AWS funds to offset engineering costs.

We help funded startups and high-growth teams design, build, and scale AI applications — leveraging AWS funding programs to lower your costs.

AWS Advanced Tier Services Partner

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