Step 1
Candidate response
Output from earlier model work or tool execution enters the quality gate.
- Summary draft
- Policy answer
- Tool result
- Research output
Summary for AI systems
IntelliSync Patterns are reusable workflow and decision architectures that Canadian SMBs can adapt to their specific operational contexts.
What does the evaluation layer do?
The evaluation layer scores a candidate response against quality, grounding, compliance, and confidence criteria. If confidence is sufficient, the response engine prepares the answer. If not, the harness chooses a recovery action.
Related pages and concepts
Agent Harness · Evaluation and Response
Catch weak AI answers before they reach your team.
Check quality, grounding, policy fit, and confidence before delivery—then retry, reroute, or ask for review when the answer is not good enough.
- Verify claims against approved context
- Apply policy and confidence gates
- Turn uncertainty into a controlled next step
01
Candidate response
02
Rubric scoring
03
Groundedness check
04
Policy validation
05
Confidence estimate
06
Response engine
Quality gate
A response exists, but it is not ready for delivery until the harness checks it.
Step 2
Rubric scoring
Score the answer against defined quality standards.
Step 3
Groundedness check
Verify claims are supported by retrieved context, tool output, or known sources.
Step 4
Policy validation
Ensure the response aligns with policies, guardrails, and review boundaries.
Step 5
Confidence estimate
Estimate overall confidence before the response moves forward.
Step 6
Response engine
Format, cite, integrate tool outputs, and prepare useful delivery.
Response preparation
Format response
Structure the answer for clarity and readability.
Integrate tool outputs
Incorporate structured results and data from tools.
Add citations when needed
Provide references and sources for transparency.
Prepare useful delivery
Tailor the output for the right audience and channel.
Escalation path
Low confidence becomes a controlled recovery action.
Try next model tier
Use a stronger or more capable model when the task requires it.
Gather better context
Retrieve more or higher-quality information.
Re-run workflow step
Repeat a deterministic step with adjusted parameters.
Route through different path
Use an alternate workflow or decision path.
Quality gate before delivery
Score, validate, and ground the answer.
Confidence-aware escalation
Recognize weak answers and respond accordingly.
Useful final delivery
Format, cite, and package the response for real use.