Sources & access
Start with the source systems, who may read each source and which questions the product should answer.
Awakast · AI engineering
RAG development services
For CTOs and product owners whose users need answers grounded in company documents, we add a RAG-powered answer flow to your existing product, with citations and access controls matched to user roles.
Discuss your RAG integrationDefine the scope
Define the evidence and review flow before choosing a retrieval stack
Evidence & review
Agree how an answer refers back to its evidence, what needs human review and what happens when the sources do not support an answer.
Evaluation first
Scope evaluation before choosing the retrieval stack.
What you can commission
Agree the sources, user groups and first answer flow before implementation. The following is a starting scope to adapt to your product, not a fixed package.
A source and permission map
Document the systems to connect, source owners, allowed user roles and update rules. Define what stays outside retrieval, including material a user is not entitled to see.
An integrated answer flow
Scope ingestion, retrieval and answer generation inside the existing product. Include source references, an explicit insufficient-evidence response and a review interface where the user needs to approve a draft.
Tests and an operating brief
Agree a reusable question set, expected evidence and acceptance checks. Agree the handover contents before we start, including configuration, source-refresh instructions, monitoring and operating instructions for your technical team.
A concrete starting point
Review contract clauses against a defined checklist
1
Hypothetical contract-review flow: retrieve the relevant clause and amendment history, cite each source, then compare the text with a reviewer-defined checklist.
2
Flag missing or conflicting terms for legal review.
3
Test clear answers, missing amendments and conflicting versions; the system drafts no legal conclusion.
Scope & acceptance
What the engineering scope can include
- Knowledge-base integration, retrieval-pipeline design, model selection, human-review points and evaluation against agreed questions.
- Plan monitoring, cost checks and an operational handover with a named owner.
- Agree source-update handling and access boundaries in the brief rather than after the first demo.
How we approach the work
Inspect the knowledge
Review representative documents and user questions together. Check conflicting versions, document structure and permissions before deciding whether RAG is the right approach.
Test retrieval separately
Check whether the permitted passage is found before judging the final answer. Compare retrieval and model options on the same questions; a larger model cannot substitute for missing source material.
Integrate and review
Build the agreed answer flow, test it with the product owner and plan a controlled release. Keep later source collections or user groups outside the first release unless separately agreed.
Controls, evaluation & ownership
Evidence and acceptance
Review answer accuracy, source support and abstention on unanswerable questions. Include outdated documents, conflicting evidence and attempts to elicit restricted content in the evaluation set.
Failure and fallback
Agree what users see when retrieval, a source system or the model is unavailable. An unsupported answer should not silently become a confident recommendation; offer search or a reviewer handoff instead.
Updates and ownership
Name the source owner and technical operator. Agree refresh checks, deletion handling, logging boundaries and who retests quality after a document, prompt or model change.
Before we start
Bring these inputs to the first conversation
Send representative questions, sample source material you may share, the source-system owner, user roles and deployment constraints.
Name the current failure: missing evidence, incorrect retrieval or time spent searching.
If usable data or feasibility is still uncertain, start with discovery; if you need actions across systems, scope a workflow instead.
When to choose another path
- No usable source material, no permission to process it or no owner for its accuracy: resolve those gaps through discovery first.
- A standard search or existing knowledge-base feature already meets the need: compare that option before commissioning a custom integration.
- The main requirement is to write records or trigger actions across systems: define the automation and approval scope as well as retrieval.
Questions before you commission
Do we need a new knowledge base?
Not necessarily. Start with the sources you maintain today. The brief should identify required connectors and any cleaning or restructuring; it should not assume a migration before reviewing the material.
Can RAG eliminate incorrect answers?
No. Source references help reviewers inspect the answer, but retrieval and generation still need testing. Agree when the system should decline to answer and which outputs need human review.
Can you work with private data?
Discuss permitted processing, deployment options, access controls and retention before sharing sensitive samples. Private hosting is an option to assess, not a blanket assurance that every architecture meets your obligations.
What determines cost and delivery time?
Source-system access, document quality, permission complexity, evaluation coverage and deployment constraints change the scope. Agree the estimate after those dependencies are understood; ongoing model and infrastructure costs belong in that discussion too.
Explore our document and knowledge integrations
Use our engineering cases to discuss source access, answer review and integration into your product.
Scope answers from your company documents
Send your product context, sample questions and source details. We will discuss the integration scope or the discovery needed to establish it.