AI Retrieval Evaluation
Find why the right evidence is missing from an agent’s answer. Evaluate retrieval, grounding and context assembly against representative tasks.
Find where supporting evidence drops out of the answer
- Candidate retrieval
- Check whether relevant permitted records are found.
- Context selection
- Track what survives ranking and truncation.
- Source conflict
- Record freshness and contradictory evidence.
- Grounded answer
- Compare assertions and citations with supplied context.
Decision and fit
Find where supporting evidence drops out of the answer
Compare the engagement with the decision you face
- A question worth resolving
- Find where supporting evidence drops out of the answer.
- An accountable participant
- Retrieval and application owners whose agents miss relevant evidence, use stale context or answer without support.
- Inspectable source material
- The relevant owners can make workflow evidence and agreed inputs available for examination.
- A scope mismatch
- The primary failure is external tool execution after the answer is formed.
The engagement
Find why the right evidence is missing from an agent’s answer. Evaluate retrieval, grounding and context assembly against representative tasks. A focused evaluation of retrieval, context assembly and grounding for a named corpus and workflow.
The decision at stake
Answer quality varies, and the team cannot separate retrieval misses from context selection or generation failures.
Suitable situations
- Retrieval and application owners whose agents miss relevant evidence, use stale context or answer without support.
Less suitable situations
- The primary failure is external tool execution after the answer is formed.
Engagement boundary
Agree the work and its boundaries together
The engagement boundary
- Candidate retrieval
- Build representative cases for retrieval relevance and evidence coverage.
- Context selection
- The inputs, authorised access and client participants are confirmed before scheduling.
- Retrieval owner
- Retains organisational decisions and risk acceptance.
- Additional implementation
- Corpus cleanup, retrieval implementation and tuning across new domains are separate work. Evaluation cases should be maintained when the corpus, permission model or context assembly changes.
What the work covers
- Build representative cases for retrieval relevance and evidence coverage.
- Examine context selection, truncation, conflicting sources and grounding.
- Separate retrieval failures from generation errors and prioritise further tests.
Scope boundaries
- Formal certification, legal conclusions and guarantees of safe or compliant behaviour.
- Implementation or ongoing operation beyond the agreed scope.
- Corpus cleanup, retrieval implementation and tuning across new domains are separate work. Evaluation cases should be maintained when the corpus, permission model or context assembly changes.
Working sequence
How the work moves from question to handover
What each stage should leave your team with
- Define answerable questions
Questions connected to authorised supporting passages.
- Measure retrieval coverage
Evidence of ranking, coverage and permission behaviour.
- Follow context into the answer
A trace from retrieved content to supported claims.
- Separate causes and retests
Stage-specific failures and regression cases.
How the work proceeds
- Define answerable questions. Select representative information needs and identify which sources can legitimately support each answer.
- Measure retrieval coverage. Inspect returned documents and ranking against relevance and permission expectations.
- Follow context into the answer. Examine selection, truncation, conflicting passages and whether claims remain supported after generation.
- Separate causes and retests. Classify failures by stage and provide focused regression cases for the corresponding engineering changes.
Decision artefacts
Leave a record the next owner can use
Grounding case
Illustrative working format
- Subject and version
- Identify the workflow, configuration or proposal examined.
- Candidate retrieval
- Record the relevant requirement and supporting material.
- Source conflict
- State the observation, supporting evidence and remaining uncertainty.
- Retrieval owner
- Record the next decision, follow-up and unresolved question.
What the work can produce
- Retrieval and grounding cases
- Context failure analysis
- Coverage and remediation backlog
Worked situation
Follow one situation through to a bounded next decision
Illustrative working situation
Illustrative scenario
- Starting condition
The retriever finds a policy that is absent from final context.
- Question to examine
Inspect retrieval candidates, selected context and answer.
- Possible next action
Target the selection failure before changing the generator.
Working together
Your team and our team need a clear working agreement
Who contributes and who decides
- Client sponsor
- Confirms the decision, priorities and people needed to resolve it.
- Client technical or process owner
- Provides the agreed evidence, access and review of findings or deliverables.
- Softlander delivery lead
- Coordinates the agreed activities, review points, handover and open actions.
- Authorised decision-maker
- Accepts deliverables against the agreed criteria and separately decides operational or business action.
What the work depends on
- A corpus owner and domain expert provide approved documents, access rules, representative questions and expected supporting passages. Engineering supplies retrieval traces, ranking settings and context-construction configuration.
Engagement availability
The start date, named delivery roles, review points and fee basis are agreed after confirming the inputs and scope. Duration depends on evidence access, system complexity and the time your decision-makers need to review the work.
Engagement and handover
Agree the delivery model and what completion means
A clear agreement from scope to ownership
- Scoped work
- Build representative cases for retrieval relevance and evidence coverage.
- Indicative handover
- Retrieval and grounding cases; Context failure analysis
- Review and acceptance
- Review the agreed deliverables and record any open items, owners and conditions.
- Ongoing work
- Assign maintenance and operational ownership; agree additional scope and coverage explicitly.
A focused evaluation of retrieval, context assembly and grounding for a named corpus and workflow.
The handover distinguishes retrieval misses, context loss and unsupported generation using traceable cases. The team receives the query set, evaluation criteria and prioritised failure analysis with corpus/version assumptions.
Corpus cleanup, retrieval implementation and tuning across new domains are separate work. Evaluation cases should be maintained when the corpus, permission model or context assembly changes.