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Find the routineWe identify where employees lose time: searching, standard emails, instructions and materials.
Business automation → AI assistants for the team
AI assistants for the team
AI assistant for employees: search across policies and documents, drafts of emails and materials, role-based access. Implemented in Kazakhstan in Russian and Kazakh.
Discuss your projectOverview
AI assistant for employees: the service in brief
Gotomarket implements AI assistants for teams in Kazakhstan. The assistant finds answers in internal documents, helps prepare emails and materials, and shows the source of each answer. The result: less time spent on searching and routine work, faster onboarding and access to knowledge without digging through chats.
- Launch
- 2–4 weeks
- Languages
- Russian and Kazakh
- Access
- by role
- Sources
- documents and knowledge bases
In plain wordsWhat it is and why it matters
- What it is
- An internal assistant for staff: it finds answers in company policies and documents, helps draft emails and materials, and shows which document each answer comes from.
- Who it is for
- Companies where staff spend time searching documents and chats, the same questions repeat across departments, and bringing new hires up to speed depends on a few people.
- What you get
- An assistant for the selected department, an organized document base, search with source links, role-based access, a query log for oversight and a plan to extend to other departments.
- Where to start
- Tell us which recurring task takes your team the most time and where the relevant documents are stored. We will suggest a trial run in one department.
Solution architecture
How we implement an AI assistant using the 5D methodology
We start with one recurring task where the team loses time and expand the scenario only after its value is proven.
Design
Choose sources and rolesWe define the documents, access rights, answer rules and quality criteria.
Deploy
Build the assistantWe connect document storage, role-based access, a query log and source links.
Drive
Run the pilotWe test the assistant in one department and measure time saved and answer quality.
Dominate
Roll out to the teamWe add departments and tasks based on feedback and proven results.
Unit economics and ROI
How an AI assistant pays off
The economics come from the time employees spend searching and writing repetitive texts. In a hypothetical example, a 10-person department spends about 200 hours a month on such work.
If the assistant cuts routine work by 30–40%, the team frees up 60–80 hours a month. Actual results depend on document quality, task frequency and how readily employees adopt the tool.
- Example department
- 10 people
- Routine work
- about 200 hours a month
- Routine reduction
- 30–40%
- Time freed up
- 60–80 hours a month
Result
What you get
After the pilot you keep a working tool, prepared knowledge and clear rules for access and further development.
- Map of recurring tasks
- Knowledge source list and audit
- Prepared document base
- AI assistant for the selected department
- Search with source references
- Role-based access and query log
- Quality test suite
- Pilot metrics and expansion plan
Comparison of approaches
Assistant vs. standard search
The tools differ in how complete the answer is and what they require from source documents.
| Approach | What it does | Limitation | Best for |
|---|---|---|---|
| Folder search | Finds a file by name | Doesn't compose an answer | Few documents with a clear structure |
| Knowledge base search | Finds matches in the text | Requires manual reading | Sources are well organized |
| AI assistant | Prepares an answer and shows the source | Needs roles and quality control | Many recurring requests |
Limitations and risks
When you don't need an AI assistant
An assistant pays off where knowledge is organized and tasks repeat.
No organized documents
If knowledge isn't collected and kept up to date, the sources need to be put in order first.
Tasks are always unique
Where every request needs a fresh expert judgment, automating search adds little value.
The team is very small
With one or two employees, the time saved may not justify implementation and support.
A good fit
When this service is a good fit
- Employees regularly look for answers in documents
- The same questions come up across departments
- Onboarding depends on specific people
- You need controlled access to knowledge
Not a fit
When to choose another approach
- Documents are scattered and quickly go out of date
- Most tasks are unique
- The team is one or two people
- A basic search over a small document base is enough
Terms in plain words
- AI assistant
- a helper that answers based on approved documents
- Role-based access
- each employee sees only the data they are allowed to access
- Answer source
- the document the assistant's answer is based on
- Query log
- history of questions and answers for oversight
- Onboarding
- getting a new employee up to speed
- Pilot
- A trial run of the assistant in one department on one task, to measure time saved and answer quality before rolling it out further.
- Quality tests
- A prepared set of questions with known correct answers, used regularly to check that the assistant is not making mistakes.
- Model provider
- The company whose AI model generates the assistant's answers; its terms determine where data is processed and which documents can be connected.
Frequently asked questions
AI assistants for the team: FAQ
Will the assistant have access to all data?
No. Permissions are assigned by role, and queries and answers can be logged for oversight.
Will the assistant replace specialists?
No. It takes over the mechanical part: searching and drafting. Decisions and expert judgment stay with the employee.
Which sources can be connected?
Policies, instructions, knowledge bases, documents in Google Drive or Notion and other accessible storage.
How long does implementation take?
A pilot in one department usually takes 2–4 weeks: preparing sources, setting up roles and testing on real tasks.
How much does an AI assistant for employees cost?
The cost depends on the number and condition of the sources, the number of roles and departments, and the integrations required. We start with a pilot in one department on one recurring task. We provide an estimate after auditing the documents and access rights.
Can an AI assistant work with tasks in Jira or Plane?
Yes. The assistant can find tasks and their descriptions, prepare project summaries and draft new tasks from task tracker data while respecting user permissions. Actions that change data, such as creating or moving a task, are carried out only after the employee confirms them. The exact set of actions is agreed during the pilot.
Can an AI assistant be connected to Twenty or amoCRM?
Yes, if managers need to quickly find a customer's history and deal terms, or draft an email based on CRM context. The assistant gets access only to approved fields and shows which record the answer comes from. Sensitive data can be excluded from the setup entirely.
Is it safe to upload internal documents to an AI assistant?
Safety depends on the architecture: which sources are connected, who has access to them, where the data is stored and what terms the model provider sets. Before launch we define the list of approved documents, the roles and query logging. Documents that must not go to external services stay outside the setup, or we choose a suitable hosting option.
Is an AI assistant a good fit for an IT product team or IT studio?
Yes. Typical tasks include searching technical documentation and the support knowledge base, drafting replies to customers, writing release notes and onboarding new developers and managers. The effect is stronger when documentation and tasks in the tracker are kept up to date.
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