Case Studies | SaaS B2B

Expert guidance for the platform stack

A SaaS B2B client

About

A SaaS B2B business working with Cloud Combinator on AWS. The client is anonymised at their request.

Challenge

The advisory engagement centred on three focus areas.

Validating the platform architecture

The client needed to confirm that their intended approach to the voice stack was sound and suited to production use. Real-time voice AI places tight demands on latency and orchestration, so an early sense-check of the design reduced the risk of costly rework later.

Choosing the right AWS building blocks

With many possible services and patterns available for conversational voice, the team wanted grounded guidance on which AWS components

De-risking next steps without a full build

As an early-stage company, the client needed maximum insight for minimum commitment. The challenge was to translate senior expertise into practical next steps quickly, keeping the engagement advisory and tightly time-boxed while still moving the product forward.

Solution

3 days

Time-boxed senior advisory effort

Weekly

Standing catch-up cadence, plus ad-hoc check-ins

2

Named advisors, primary plus backup cover

By the numbers:

  • 3 days - Time-boxed senior advisory effort
  • Weekly - Standing catch-up cadence, plus ad-hoc check-ins
  • 2 - Named advisors, primary plus backup cover
Changes

The advisory time-box was delivered as agreed, including the standing weekly catch-up. The client's technical lead received sufficient guidance to move forward, and the engagement confirmed that the recommended AWS approach and environment were suitable for the continued development of the client's service.

  • Direction validated — The client gained an experienced view on the platform architecture, confirming a sound basis for continued development.
  • Clearer AWS approach — The team came away with practical guidance on the AWS services and environment best suited to their voice stack.
  • Minimum commitment, maximum insight — The advisory-only, tightly time-boxed model gave the founder senior input without the overhead of a full build engagement.
  • Transparent delivery — All effort was tracked against a single ticket with a running burn-down available at checkpoints, keeping the engagement accountable.

With the direction validated and the AWS approach agreed, the client is well placed to move from advisory into delivery. Any transition from guidance to a hands-on build would be scoped separately, giving the client a clear and de-risked path to bringing their the platform to production on AWS.

AWS Stack

Amazon Chime SDK

For real-time voice and telephony integration.

Amazon Bedrock

For the generative AI models behind natural conversation.

Amazon Transcribe

For converting caller speech to text in real time.

Amazon Polly

For natural-sounding speech synthesis in responses.

AWS Lambda

For serverless orchestration that scales with call volume.

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