Internal knowledge assistant
Search policies, technical documentation and procedures, with references back to the source material.
All services
AI engineering · Portugal & international
AI connected to your business knowledge.
Build assistants that work with your documents, knowledge bases and operational systems. Retrieval-Augmented Generation (RAG) brings relevant sources into the answer, with citations and access rules designed around your organisation.
Pilot scope and budget agreed before development
Explore the scopeFrom business knowledge to a sourced answer
Approved sources
Select the documents and systems the assistant can use.
Permissions & retrieval
Find relevant information within each user's access rights.
Answers & evaluation
Show references and test answers against agreed examples.
Senior architecture in Portugal, hand-picked senior delivery team in Brazil, EU-aligned timezone.
16+ years of architecture experience100% IP transfer upon invoice settlement
Illustrative applications
Start with a useful business workflow
Illustrative starting points for discovery. We select a use case around the information, users and decisions in your organisation.
Support team copilot
Draft responses from approved support content, with a human review step before a reply is sent.
Operational document search
Help teams locate relevant information across manuals, project records and internal systems.
Scope & deliverables
The system around the model matters
The scope covers data access, retrieval, application behaviour and operations, so the pilot can be evaluated as a working business tool.
Sources & ingestion
Map document formats, connectors, ownership, refresh frequency and the content allowed into the knowledge base.
Retrieval & citations
Design search and source references, including how the assistant responds when the available information is insufficient.
Identity & permissions
Define authentication and access rules that also apply to retrieved information, including separation between teams or customers.
Evaluation & review
Agree representative questions, expected evidence and acceptance criteria. Review relevance, unsupported answers and sensitive information handling.
Integration & experience
Connect the assistant to your portal or existing workflow, with an interface and human escalation paths agreed in the scope.
Operations & usage costs
Define logging, source updates, model usage, cost visibility and the responsibilities needed to operate the system.
From discovery to delivery
Prove the use case before expanding it
Discover
Review the workflow, sample sources, permissions and constraints. Select a concrete business question to address.
Build a pilot
Agree a bounded set of sources, integrations, deliverables, price and acceptance criteria before implementation.
Evaluate together
Test agreed examples with the people who will use the tool. Record failure cases and decide what needs to improve.
Integrate & operate
Approve the production scope, deployment environment, monitoring and support plan using the evidence from the pilot.
A clear commercial agreement
Know what the pilot and ongoing operation include
- Pilot agreement
- The proposal identifies the use case, source coverage, deliverables, dependencies, budget and acceptance process.
- Model & infrastructure costs
- Model APIs, storage, indexing and hosting are itemised separately from implementation, with usage assumptions documented.
- Data & deployment
- Agree the environment, providers, data handling and retention requirements before connecting business information.
- Support & changes
- Source maintenance, monitoring and support have a defined scope. Additional integrations or use cases are estimated and approved before work starts.
Software in daily production
Explore our client work
See the operational software behind our engineering experience, from fleet management to automotive SaaS.
Before we start
Questions about AI and RAG projects
What is RAG, in practical terms?
RAG retrieves relevant content from selected sources before a model produces an answer. It can connect an assistant to company knowledge and provide source references, while the application controls access and the user experience.
Can the assistant respect our existing permissions?
Permissions are part of discovery and design. We define how identity and source access apply during retrieval, then test access boundaries during evaluation.
How do you assess answer quality?
We agree a set of questions and expected evidence, test the assistant against them and review unsupported or incomplete answers. Citations help users inspect the evidence; acceptance depends on the criteria agreed for the use case.
Can you integrate with our current software?
We review the systems, APIs and authentication available during discovery. The pilot and proposal identify which integrations are included and any access or licensing dependencies.
How much does an AI pilot cost?
We prepare a proposal after reviewing the use case and sources. It separates implementation from model usage, infrastructure and optional support, so you can approve a defined scope and budget.
Talk directly to engineering leadership
Bring a workflow and a sample of your knowledge sources.
Tell us who needs the assistant, where the information lives and what a useful answer should look like. We will use that context to discuss a practical pilot.
Book a callPrefer email? contact@caravelsoftware.eu
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