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Curious Context Labs

case study · Company-wide · Company assistant

A company assistant that answers from your own documents, with sources

How an assistant connected to your drives and wikis can answer staff questions, respect permissions and show which documents are missing.

business
Manufacturing
build
Company assistant
timeline
5 weeks
read
3 min

01 the business

Engineering and surveying firm

180 staff across five offices

Staff ask the same questions daily: where the latest rate card is, how to set up a site visit, which template to use. The answers sit in SharePoint, Google Drive or a senior colleague's head. Experienced people are interrupted all day, and new starters guess.

02 before

The problem

Staff ask the same questions every day: where the latest price list is, how to handle a refund, what the process is for a site visit. The answers sit somewhere in SharePoint, Google Drive or a senior colleague's head, so experienced people get interrupted all day and new starters guess.

  • Senior staff answer the same questions repeatedly.
  • New starters take months to find their way around.
  • Out-of-date documents are used by mistake.

03 the build

What the AI does

  1. Step 1: Connects to the places your knowledge lives, such as SharePoint, Google Drive, Confluence, Notion and your help centre, and keeps their existing permissions.
  2. Step 2: Indexes the content and refreshes it as documents change, so answers reflect the current version.
  3. Step 3: Answers questions in plain language inside Slack, Microsoft Teams or a web page, citing the documents it used.
  4. Step 4: Says clearly when it cannot find an answer and points to the right person or team to ask.
  5. Step 5: Logs unanswered and frequent questions so owners can see which documents are missing or out of date.

paused: waiting for a person to approve

How it was put together

  • Connected SharePoint, Confluence and the help centre, keeping existing permissions.
  • Indexed content and refreshed it as documents changed.
  • Answered in Teams, citing the documents used.
  • Logged unanswered and frequent questions for knowledge owners.

04 human in the loop

Where a person stays in charge

A named owner for each knowledge area approves which sources the assistant may use and reviews the gap report each month. The assistant only answers questions; it does not change records or send anything outside the company.

  • Each knowledge area has an owner who approves sources.
  • The assistant only answers; it never changes records or sends anything outside.
  • Staff only see answers from documents they can already open.

05 rollout

From kickoff to live in 5 weeks

  1. Weeks 1–2Choose sources and owners; retire outdated documents.
  2. Week 3Pilot with one office.
  3. Weeks 4–5Roll out firm-wide with a monthly gap review.

06 after

What changes

People find answers without waiting for a colleague, and the experienced staff who used to field every question get their time back. Gaps in your documentation become visible and get fixed.

worked example · your numbers will differ

Assume 180 staff each spending 30 minutes a week looking for information or asking colleagues, and the assistant saving a third of that.

180 × 10 minutes = 1,800 minutes, or 30 hours a week returned to billable and project work.

What to measure

  • Questions answered with a citation.
  • Interruptions to senior staff.
  • Gap-report items fixed each month.
  • New starter time to productivity.

07 evidence

What the research says

  1. In a survey of 31,000 people in 31 markets, 75% of knowledge workers said they use AI at work, and 78% of AI users bring their own AI tools.

    Microsoft and LinkedIn, 2024 Work Trend Index: AI at work is here. Now comes the hard part (opens in a new tab) · 2024

  2. Knowledge workers spend roughly a fifth of their working week searching for and gathering information.

    McKinsey Global Institute, Capturing business value with social technologies (opens in a new tab) · 2012

  3. Across 5,179 customer support agents, an AI assistant raised issues resolved per hour by 14% on average and by 34% for novice and lower-skilled agents.

    NBER, Generative AI at Work (Brynjolfsson, Li and Raymond) (opens in a new tab) · 2023

08 lessons

Mistakes to avoid

  • Indexing everything. Old files cause wrong answers.
  • No owners. Gaps never get fixed.
  • Ignoring permissions.

09 questions

Common questions

Do staff already use AI?
Microsoft and LinkedIn found 75% of knowledge workers use AI at work, and 78% of them bring their own tools. A company assistant gives them a safe option grounded in your documents.
Is our data used to train models?
We use business-grade AI services that do not train on your data, with accounts in your name.

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