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Make approved knowledge easier to find and use.
Create retrieval-based search and question answering over the information your users are allowed to access. Design document ingestion, source references and access rules together.
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Overview
Enterprise Knowledge Search, explained
Retrieval-augmented generation, or RAG, lets people ask questions in plain language and receive answers drawn from your own documents, with links to the sources. It is the practical way to make policies, manuals, contracts and project files searchable without retraining a model every time a document changes.
Most of the quality comes from the retrieval side: how documents are cleaned, split, indexed and filtered by permission. We build that pipeline carefully, test it with real questions from your team and show sources with every answer so users can verify before they rely on it.
Before you build
Decisions worth settling first
Settling these points early keeps scope realistic and makes the estimate meaningful.
01
Document sources
List repositories such as SharePoint, Google Drive, Confluence or file shares, and their formats.
02
Access rules
Confirm who may see which documents so answers never expose restricted content.
03
Test questions
Collect real questions with known correct answers to measure retrieval and answer quality.
04
Freshness
Decide how quickly new or changed documents must appear in answers.
05
Answer style
Agree length, citation format and what the system says when it cannot find an answer.
06
Hosting and data residency
Choose where indexes and models run to meet your security policy.
Services
What our enterprise knowledge search services include
Knowledge base assistants
Question answering over internal documentation for staff with cited sources.
Customer-facing help search
Answers from public help content inside your website or app.
Document ingestion pipelines
Connectors, parsing, OCR, chunking and metadata enrichment for mixed document sets.
Permission-aware retrieval
Filtering results by user, group or document labels at query time.
Hybrid search
Combining keyword and vector search with re-ranking for precise results.
Quality evaluation
Measurement of retrieval accuracy and answer faithfulness with ongoing test runs.
How it is built
The layers behind a dependable result
Every layer has an owner, tests and documentation, so the system can be supported after launch.
01
Ingestion
Connectors and parsers that turn documents into clean text with metadata.
02
Indexing
Chunking, embeddings and keyword indexes tuned to your content.
03
Retrieval
Hybrid search, permission filters and re-ranking that select the best passages.
04
Answering
Model prompts that answer only from retrieved sources and show citations.
Use cases
Where it helps
HR and policy questions
Staff find leave, expense and policy answers without opening a ticket.
Technical documentation
Engineers and support staff search manuals and runbooks.
Sales enablement
Teams find past proposals, product details and approved wording.
Legal and contracts
Locate clauses and obligations across agreements with references.
Project knowledge
Search meeting notes, specifications and decisions across projects.
Customer help centre
Customers get precise answers from your help articles.
Illustrative use case
An internal assistant can find relevant policy passages and show the source instead of asking employees to search multiple folders.
Why PoliteTech
Why teams choose PoliteTech
Scope before commitment
Priorities, assumptions and acceptance criteria are agreed in writing before a delivery plan is fixed.
Engineers who build
Recommendations come from the people who design, code and support the software, so they reflect real implementation effort.
Visible progress
A shared backlog, regular demos and recorded decisions keep you informed without chasing updates.
Practical AI
Evaluation sets, review steps, cost limits and monitoring are part of every AI feature we ship.
Flexible engagement
Start with a scoped project, a dedicated team or support, and change the model as your roadmap evolves.
Clear ownership
Repositories and accounts can live in your organisation, with IP and confidentiality terms agreed in the contract.
Industries
Where this work fits
Retail and Ecommerce
Build web and mobile journeys around product discovery, ordering and customer service.
Financial Software
Support reporting, document processing and internal operations through defined application workflows.
Logistics Software
Connect planning, task assignment and operational updates in one workflow.
Education and Elearning
Create platforms for content, activities and progress tracking.
Fitness and Wellness Apps
Support tracking, coaching content and user engagement around a clear product goal.
Manufacturing Software
Replace fragmented tracking with workflows for quotations, work status and supporting documents.
Real Estate Applications
Create listing, enquiry and internal coordination tools around your business process.
Business Operations
Build task, approval and reporting tools around the way your team works.
Process
A practical path from requirements to release.
Each stage ends with something you can review: a scope, a prototype, a working increment or a release.
01
Understand
Discuss your users, business needs, existing systems and delivery constraints.
02
Define
Agree scope, technical approach, responsibilities and a delivery plan.
03
Design and build
Develop in manageable increments with visible progress and review points.
04
Test and release
Validate agreed workflows, resolve release blockers and prepare deployment.
05
Support and improve
Document the handover, review production feedback and plan the next priorities.
Technology
Tools and platforms we work with
PythonLlamaIndexLangChainOpenAIGoogle GeminiLlamaMistralElasticsearchOpenSearchpgvectorQdrantAzure AI SearchUnstructuredTesseract OCRFastAPIReact
Cost
What shapes the cost of your project?
There is no useful price without scope. These are the factors we review when preparing an estimate, and the estimate lists every assumption so you can see what would change it.
01
Number of workflows
Each workflow needs its own prompts, tools, evaluation set and review design.
02
Data preparation
Cleaning, labelling, chunking and access rules often take more effort than the model itself.
03
Integrations
Connections to CRMs, ERPs, document stores and identity providers add design and testing work.
04
Evaluation and review
Building test sets, review queues and monitoring is essential for reliable results.
05
Model and hosting
Hosted APIs, open models and private deployment have very different setup and running costs.
06
Security and compliance
Sensitive data, audit needs and data residency add controls and documentation.
Engagement models
Choose the engagement that fits your next step.
Dedicated Team
For a changing roadmap or ongoing development. Agree roles and working process, then manage priorities through a shared backlog.
Best for team extension and long-term product work.
Scoped Project
For a defined product or milestone. Align on requirements, deliverables and acceptance criteria, with changes reviewed before they affect the plan.
Best for MVPs, integrations and focused releases.
Maintenance and Improvement
For software that already exists. Start with a technical review, then agree support routines and planned improvements.
Best for live applications and modernisation.
FAQ
Questions about enterprise knowledge search
How is RAG different from a normal search?
Search returns a list of documents. RAG reads the most relevant passages and writes an answer, with links to those passages so you can check them.
Will it make up answers?
We instruct the model to answer only from retrieved sources, show citations and say when information is not found. Evaluation tests check faithfulness.
Can it respect document permissions?
Yes. Permissions are applied during retrieval, so users only receive answers from documents they are allowed to see.
Which document types are supported?
Common formats include PDF, Word, PowerPoint, HTML, wiki pages and scanned files through OCR.
Can it run in our own cloud?
Yes. Indexes and models can run in your AWS, Azure or Google Cloud account, including with open models.
How do you measure quality?
We use a test set of real questions to measure whether the right passages are retrieved and whether answers stay faithful to them.
Can we begin with a focused scope?
Yes. We can review your current situation and agree a bounded first engagement before a wider build.
How are pricing and timelines determined?
We review requirements, technical complexity, team needs and delivery constraints before proposing an engagement. Estimates list assumptions and what may change the plan.
Can we discuss a project under an NDA?
Yes. Let us know before sharing confidential materials so we can agree confidentiality terms first.
Discuss your enterprise knowledge search needs
Share your goals, current situation and the help you need. We will review your message and suggest a practical next step.