Automat-it LLM Selection Optimizer
Automat-it LTD · Software Development
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 4 captures on record
What the publisher says
As described on AWS Marketplace.
Choosing the right Large Language Model (LLM) for your workload is a decision that directly impacts your application's performance, accuracy, and operational costs.
Many organizations default to the largest, most capable models—assuming bigger means better—only to discover they're overpaying or using the largest models for all tasks, reducing profitability.
Show the rest of the publisher’s description (4 more lines)
The LLM Selection Optimizer is a fixed-scope engagement where Automat-it benchmarks your actual production data against Amazon Bedrock's model catalog to identify the optimal model (or combination of models) for your specific use case.
Unlike generic model comparisons, this engagement uses your real datasets and workflows to measure what matters: latency, accuracy, throughput, and cost-per-request for your workload.
Our team analyzes whether complex tasks can be decomposed into simpler sub-tasks handled by lighter, faster models. A technique that frequently reduces inference costs by 40-60% while maintaining or improving response quality. The deliverable is a comprehensive report with quantified performance metrics, cost projections, and a clear recommendation for your Amazon Bedrock implementation.
Automat-it brings deep expertise in generative AI and machine learning across industries, with a team of ML engineers and data scientists who have optimized LLM deployments for startups at every stage. We handle the technical heavy lifting, you provide the data and requirements, and you receive actionable intelligence to make a confident, data-backed model selection decision.
Highlights
Highlighted by the publisher on AWS Marketplace.
Receive a Benchmarking Report and data-backed recommendation to confidently deploy the model that maximizes ROI
Optimize Burn rate: Use right-sized models to avoid wasted spend
Faster Time-to-Decision: Skip trial-and-error cycles with standardized, reproducible benchmarks
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment
Sources
Publisher resources
2 linksLinked repositories
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