Their engineers were propping up overprovisioned LLM clusters instead of shipping. Bedrock took the upkeep; the team got back to building.
A research services and AI products company with 4,000+ experts, developing writing, discovery, and editorial tools for researchers, publishers, and life science organizations across eight global offices.
Building LLM-powered products in-house required running training and inference clusters that needed significant overprovisioning to maintain...
“With LLMs advancing worldwide, we recognized a clear opportunity to concentrate on building generative AI services that meaningfully enhanced our portfolio.”
Scientific communication and technology services for researchers and life sciences.
Cloud computing platform and on-demand infrastructure services.
Cactus Communications's Product development is part of this use case:
Related implementations across industries and use cases
Manual ad production took months. Now, teams use AI to predict performance and generate creative in just 5 days.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Processing trillion-token datasets took months. A native vector engine cut deduplication costs 5x and doubled processing speed.
Dedicated servers sat idle between training runs. Now, engineers spin up compute on demand, eliminating costs for inactive time.
Privacy rules bottlenecked AI scaling. A secure internal platform now cuts AML investigation time by days and security resolution by 50%.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Their engineers were propping up overprovisioned LLM clusters instead of shipping. Bedrock took the upkeep; the team got back to building.
A research services and AI products company with 4,000+ experts, developing writing, discovery, and editorial tools for researchers, publishers, and life science organizations across eight global offices.
Building LLM-powered products in-house required running training and inference clusters that needed significant overprovisioning to maintain...
“With LLMs advancing worldwide, we recognized a clear opportunity to concentrate on building generative AI services that meaningfully enhanced our portfolio.”
Scientific communication and technology services for researchers and life sciences.
Cloud computing platform and on-demand infrastructure services.
Cactus Communications's Product development is part of this use case:
Related implementations across industries and use cases
Manual ad production took months. Now, teams use AI to predict performance and generate creative in just 5 days.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Processing trillion-token datasets took months. A native vector engine cut deduplication costs 5x and doubled processing speed.
Dedicated servers sat idle between training runs. Now, engineers spin up compute on demand, eliminating costs for inactive time.
Privacy rules bottlenecked AI scaling. A secure internal platform now cuts AML investigation time by days and security resolution by 50%.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.