COMPANY KNOWLEDGE & DATA

Find the answers. See what supports them.

We build intelligent search across documents and knowledge bases, alongside AI interfaces for analyzing structured data. Users get answers linked to sources or an explanation of a metric, rather than an unsupported guess.

Discuss search and data Explore the examples

Sources, freshness and permissions are part of the solution.

Search interface with an answer and linked source cards.

ANSWERS YOU CAN INSPECT

Find a rule. Explain a metric.

Searching documents and analyzing tables are different tasks. Here is how each can work through a clear interface.

Where should project materials be stored?

Supported by two demonstration sources

Store the materials in the shared workspace for that project. Ask the project owner to arrange access for a new team member.

Material storage guide Team access guide

Example sources

Material storage guide

Demonstration version 1

“Materials are stored in the shared workspace for the relevant project.”

Team access guide

Demonstration version 1

“The project owner approves access for new team members.”

Prepared examples using fictional data.

An answer should leave a path to verification: a document passage, a record or an understandable calculation.

Two capabilities in one workspace

Search helps people find meaning in materials. Analysis works with defined fields, metrics and calculation rules.

Find and explain

Search by meaning
Find relevant passages even when the question does not repeat the document’s title.
Answers with sources
Show the material supporting an answer and let users inspect the relevant passage.
Questions about structured data
Turn agreed questions into validated data selections and calculations, with explicit metric definitions.

Maintain quality

Permission-aware retrieval
Limit retrieval and answer context to the materials the user is permitted to access.
Source updates
Account for new versions, deletions and access changes so the search index stays aligned with the source material.
Coverage and accuracy evaluation
Evaluate whether the right passages are found, whether the answer matches them and how the system handles insufficient information.

Good search starts with well-managed sources

A relevant-sounding answer is not useful if it relies on an outdated document or information the user should not access.

Know where the material lives
Choose the repositories and data types for the first release, with a clear owner and connection method.
Identify current versions
Define which document is current, how often the index updates and how conflicting sources are handled.
Apply access controls before retrieval
Do not rely on asking a model to hide restricted information. Permissions must limit which sources are available in the first place.

Organized documents, tables and knowledge sources with access controls and updates.

Where this kind of solution helps

Start with questions your company can already answer, but only after a difficult search.

Internal team knowledge
Instructions, policies and materials are spread across repositories. Employees need a concise answer and a route to the original source.
Preparing a customer response
A support agent needs a specific detail from product documentation. Search can surface relevant explanations without taking the employee’s decision away.
Understanding operational metrics
A manager needs to understand an agreed dataset, such as inquiry topics, task statuses or volume over a period. Transparent calculations and metric definitions matter.

How we build inspectable search

Start with sources and real questions before choosing the architecture.

01. Review the sources
Map the materials, owners, access permissions and update mechanisms.
A source inventory, access rules and update requirements.
A source inventory, access rules and update requirements.
02. Collect user questions
Record expected answers, supporting sources and questions that cannot be answered with the available information.
Reference questions and expected answers.
Reference questions and expected answers.
03. Evaluate retrieval and calculations
Test passage retrieval, source references or agreed calculations for structured data.
A prototype and evaluation results for retrieval and calculations.
A prototype and evaluation results for retrieval and calculations.
04. Embed the interface
Add answers, sources, error states and a clear way to refine a question.
An answer interface with sources and question refinement.
An answer interface with sources and question refinement.
05. Set up updates and evaluation
Test version changes, deletions, permissions and reference questions after updates.
Configured updates and reference checks.
Configured updates and reference checks.

ESTIMATE

Which sources should come first?

Start with representative questions, available materials and an understanding of who should be able to see the answers.

Discuss search and data

Questions
What do users most often need to find or explain?
Sources
Where are documents and data stored, and how often do they change?
Access rules
Which roles, teams or customers have different permissions?
Metric definitions
For analysis, which fields, periods and calculations are authoritative?

QUESTIONS & ANSWERS

Questions about AI search and data analysis

Answers with inspectable sources and explanations of metrics from defined data. Not an autonomous agent or universal forecasting.

Questions and answers

RAG retrieves relevant material before using it to compose an answer. It can be useful for company knowledge that changes over time. We assess whether it fits your sources, questions and quality requirements.

Ordinary search often returns a list of matches. Intelligent search can account for meaning and prepare an answer with sources. Some tasks only need better filters or full-text search; AI is not necessary for every query.

The system should state that information is insufficient, suggest a clarification or direct the question to an owner. We include these cases in evaluation so missing evidence is not hidden behind a confident answer.

Access rules apply to retrieval and to which sources may enter the answer context. They are enforced and tested by the application, including role changes and revoked access.

Define freshness rules: document ownership, current versions, update mechanisms and source priority. If there is no authoritative answer, the system should surface the conflict or ask for clarification.

An interface can be built around approved datasets and metrics. Access is limited, queries are checked and calculations follow explicit rules. The model is not given unrestricted write access or arbitrary command execution.

Descriptive analysis and forecasting are different tasks. A forecast needs its own dataset, methodology evaluation and error assessment. It is not automatically included in search or metric explanation work.

Yes. A pilot with one organized source helps evaluate questions, retrieval quality, permissions and updates. Additional sources can be connected after their formats and access rules are reviewed.

START WITH A QUESTION

Which answer does your teamspend too long looking for?

Show us the question and the sources that should contain the answer. We will define the search approach, permissions and first scenario to evaluate.

Discuss search and data All AI services

Find the answers. See what supports them.

Sources, freshness and permissions are part of the solution.

Two capabilities in one workspace

Search helps people find meaning in materials. Analysis works with defined fields, metrics and calculation rules.

Find and explain

Search by meaning
Find relevant passages even when the question does not repeat the document’s title.
Answers with sources
Show the material supporting an answer and let users inspect the relevant passage.
Questions about structured data
Turn agreed questions into validated data selections and calculations, with explicit metric definitions.

Maintain quality

Permission-aware retrieval
Limit retrieval and answer context to the materials the user is permitted to access.
Source updates
Account for new versions, deletions and access changes so the search index stays aligned with the source material.
Coverage and accuracy evaluation
Evaluate whether the right passages are found, whether the answer matches them and how the system handles insufficient information.

Good search starts with well-managed sources

A relevant-sounding answer is not useful if it relies on an outdated document or information the user should not access.

Know where the material lives

Choose the repositories and data types for the first release, with a clear owner and connection method.

Identify current versions

Define which document is current, how often the index updates and how conflicting sources are handled.

Apply access controls before retrieval

Do not rely on asking a model to hide restricted information. Permissions must limit which sources are available in the first place.

Where this kind of solution helps

Start with questions your company can already answer, but only after a difficult search.

Internal team knowledge

Instructions, policies and materials are spread across repositories. Employees need a concise answer and a route to the original source.

Preparing a customer response

A support agent needs a specific detail from product documentation. Search can surface relevant explanations without taking the employee’s decision away.

Understanding operational metrics

A manager needs to understand an agreed dataset, such as inquiry topics, task statuses or volume over a period. Transparent calculations and metric definitions matter.

How we build inspectable search

Start with sources and real questions before choosing the architecture.

01. Review the sources
Map the materials, owners, access permissions and update mechanisms.
A source inventory, access rules and update requirements.
A source inventory, access rules and update requirements.
02. Collect user questions
Record expected answers, supporting sources and questions that cannot be answered with the available information.
Reference questions and expected answers.
Reference questions and expected answers.
03. Evaluate retrieval and calculations
Test passage retrieval, source references or agreed calculations for structured data.
A prototype and evaluation results for retrieval and calculations.
A prototype and evaluation results for retrieval and calculations.
04. Embed the interface
Add answers, sources, error states and a clear way to refine a question.
An answer interface with sources and question refinement.
An answer interface with sources and question refinement.
05. Set up updates and evaluation
Test version changes, deletions, permissions and reference questions after updates.
Configured updates and reference checks.
Configured updates and reference checks.