Success Story

AWS MAP assessment and AI optimization for Grego AI: TCO, token-quota management and per-model cost observability

Grego AI is a generative-AI startup (operations in Argentina and Grego AI Inc. in Delaware, USA) running language models on Amazon Bedrock and OpenAI. Craftech has supported it since March 2026 with an AWS-funded assessment (Migration Acceleration Program) and optimization work on its AI consumption on AWS.

AI SaaS Mar 2026 – ongoing (AWS MAP assessment; planned Mobilize/migration phase)
AIMigracion

Challenge

Grego AI needed to organize and optimize its generative-AI operation on AWS: understand its total cost of ownership (TCO), manage token-quota limits with AWS, gain visibility into per-model consumption cost, and prepare an AWS-funded migration within tight deadlines.

Solution

Craftech structured an AWS MAP assessment: discovery documentation (current models and usage review, token-consumption analysis, critical-prompt identification and evaluation-metric definition), a total-cost (TCO) report and a migration roadmap. In parallel it ran technical work: configuring an EC2 instance for a test environment, managing token quotas with AWS, defining new quota limits, and a CloudWatch cost dashboard per model consumption, with a Mobilize-phase SOW for the migration.

Results

Grego AI has a full diagnosis of its AI operation (TCO, token consumption, critical prompts and evaluation metrics), a migration roadmap and tighter cost control thanks to the per-model consumption dashboard in CloudWatch and token-quota management with AWS. The engagement enables the AWS-funded Mobilize migration phase and a relationship that remains active.

Stack & technologies

Amazon BedrockOpenAIAmazon EC2Amazon CloudWatchAWS MapGenerative AI

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