A secure AI knowledge assistant that reduced repetitive HR and IT requests
An enterprise assistant trained on company policies gave employees trusted answers and, in pilots, cut repetitive queries and Tier-1 tickets.
The situation
Employees lose a large share of each week searching for information, and much of the rest goes on repetitive requests to HR and IT. An enterprise wanted faster access to answers without weakening control of confidential material such as contracts, HR records and financial reports.
The challenge
- Knowledge was scattered. Policies and documents lived in many systems, so retrieval was slow and inconsistent.
- Repetitive requests consumed expert time. HR and IT teams answered the same questions repeatedly.
- Public AI tools fell short. They could not meet internal requirements for access control, data isolation and governance.
What we built
A secure enterprise assistant with four properties:
- One knowledge hub. It answers from internal and approved external sources in a single place.
- Self-training on company content. It learns policies, processes and terminology directly from the organization’s own material.
- Integration with core platforms. It connects to systems such as ERP and CRM and can grow from one department to the whole organization.
- Enterprise-grade security. Role-based access, data isolation and flexible deployment options keep the assistant within governance rules.
Pilot results
| Area | Result in pilot |
|---|---|
| HR onboarding | About 30% shorter onboarding time |
| HR policy and benefits questions | About 45% fewer queries |
| IT Tier-1 support | About 50% fewer repetitive tickets |
| Operations | More consistent answers and fewer errors |
These figures are internal results, measured with our own tooling during pilot programs. Outcomes in your organization depend on your content, systems and adoption.
What others can take from this
An enterprise assistant is only as trustworthy as its content and its access controls. Start with one function, measure the requests it removes and expand from there. Our Machine Learning Engineering team can help you scope a first pilot.
Frequently asked questions
Why not use a public AI tool for internal questions?
Public tools cannot enforce an organization's access rules, data isolation or governance requirements, so confidential files and policies would be exposed to risk.
Which results did the pilots show?
In internal pilot programs measured with our own tooling, onboarding time fell by about 30 percent, policy and benefits queries to HR by about 45 percent and repetitive Tier-1 IT tickets by about 50 percent.
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