Halving resolution time without adding headcount

BTT Engineering (BEng) delivers technical projects where answers are buried in drawings, specifications and years of prior correspondence. Finding them was the bottleneck. Moterra removed it without adding a single hire.

At BEng, answering a technical query meant searching drawings, specifications and years of email history, often by asking whoever had been there longest. That put a small number of senior engineers on the critical path for routine questions, and made resolution time unpredictable. Every new hire took months to become self-sufficient.

Keyword search across the file server returned too much and ranked it badly. Public AI tools were not an option because the material is commercially sensitive and client-specific. Attempts to solve it with process - better folder conventions, a wiki - depended on people maintaining them, and did not survive contact with project deadlines.

Moterra deployed a private environment inside BEng’s own cloud, with the Internal Knowledge Assistant connected to their existing document repositories so answers are grounded in their own material and respect existing permissions. The AI Data Analyst was added for operational reporting. Moterra handled setup, MDM packaging and training, and the team was working in it in under two weeks.

Technical queries now resolve in roughly half the time, and cost per case fell because less senior time is consumed per query. Newer engineers answer questions themselves instead of queueing behind the same few colleagues, which was the outcome BEng cared about most.

What problem did BTT Engineering (BEng) need to solve?

At BEng, answering a technical query meant searching drawings, specifications and years of email history, often by asking whoever had been there longest. That put a small number of senior engineers on the critical path for routine questions, and made resolution time unpredictable. Every new hire took months to become self-sufficient.

What did Moterra deploy for BTT Engineering (BEng)?

Moterra deployed a private environment inside BEng’s own cloud, with the Internal Knowledge Assistant connected to their existing document repositories so answers are grounded in their own material and respect existing permissions. The AI Data Analyst was added for operational reporting. Moterra handled setup, MDM packaging and training, and the team was working in it in under two weeks.

What results did BTT Engineering (BEng) see?

Technical queries now resolve in roughly half the time, and cost per case fell because less senior time is consumed per query. Newer engineers answer questions themselves instead of queueing behind the same few colleagues, which was the outcome BEng cared about most.

Where does the deployment run?

Inside the client’s own cloud tenant, in the region they choose. The deployment is Private Claude Cowork by Moterra, with admin, MDM and governance handled by Moterra AI Bridge. Moterra builds in AWS and Azure, operates as a data processor under a DPA covering UK and EU GDPR, and the stack is ISO 27001 and ISO 42001 certified across the AWS and Anthropic layers.

How long does a deployment like this take?

Standard deployment is typically live within one to two weeks, covering environment and region setup, the identity path from your SSO, managed configuration through your MDM, and the connector allowlist.

Bring the hardest questions to the first call.

Thirty minutes, a live demo, and a quote for your environment.

Moterra is a private AI deployment company. We help businesses deploy Claude inside their own AWS or Azure environment, connect it to the tools they already use, and keep it secure and governed, so everyday processes get faster.

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