A real view of answer quality
Track resolution, estimated satisfaction, uncertainty, and risk. Instead of message counts, see whether the assistant actually helped the visitor.
AI answer quality assurance
Do you know what your AI assistant can really handle?
Informio Quality Lab turns anonymous chats into measurable insight. See which questions were resolved, where the assistant was uncertain, what is missing from the knowledge base, and whether a new change broke answers that already worked.
Automatic chat evaluationPrioritised knowledge gapsRegression gate before release
Informio Quality Lab
Assistant quality across real conversations
86 %
Resolution rate
4.4 / 5
Estimated satisfaction
12 %
Average uncertainty
4 %
Risky answers
Most frequent knowledge gaps7
18×
11×
6×
Regression check passed
12 / 12 tests passed
Knowing how many people asked is not enough. You need to know whether they received a correct and useful answer.
MeasureUnderstandImproveVerify
From assumptions to evidence
Quality you can see and manage
Quality Lab combines real conversation analysis, knowledge improvement, and automatic testing in one safe workflow.
Missing knowledge without guesswork
Similar unanswered questions are grouped into a knowledge gap. You can see exactly which topic is worth improving first.
Tests for AI answers
Save important questions, expected answers, and required or forbidden phrases. Informio verifies them again after every critical change.
Protection from silent regressions
Changing the model, system instructions, or knowledge base can affect old answers. Quality Gate catches the problem before a visitor does.
Priorities based on real demand
Gaps are ranked by occurrence. Your team invests time in the information customers are actually looking for.
Humans remain in control
AI prepares a draft, but an administrator verifies the facts before publishing. A failed gate can be consciously overridden with clear ownership.
Conversation intelligence
Every completed chat becomes feedback
After roughly ten minutes of inactivity, Quality Lab evaluates the complete conversation context. It does more than search for keywords—it assesses the outcome, uncertainty, and need for human intervention.
A visitor has a natural conversation
The complete anonymous widget session is evaluated, including follow-up questions—not an isolated message.
Quality Lab evaluates the outcome
It determines intent, resolution score, satisfaction, uncertainty, risk, and whether a human is needed.
It discovers missing knowledge
When an answer was missing due to insufficient data, the question is assigned to an existing topic or creates a new gap.
Your team adds verified facts
The prepared draft is reviewed and sent through the same knowledge pipeline as other sources in one step.
Evaluated conversation
Availability and delivery date
Is this product in stock and when will it arrive?
I do not have confirmed information about that yet.
Resolution score
28 / 100
Uncertainty
82 %
Needs a human
Yes
Gap found: product availability
The question is recurring, but the assistant has no stock quantity or confirmed delivery date.
Delivery time and stock
Open knowledge gap
Example question
When will a product that is not in stock arrive?
Knowledge content draft
Products in stock are dispatched within [ADD TIME]. For made-to-order products, the delivery time is [ADD VERIFIED INFORMATION].
The marked facts must be verified before saving.Create knowledge source
Knowledge gap workflow
An unanswered question becomes a concrete task
Quality Lab does not let a problem disappear into chat history. It groups similar questions, counts occurrences, and prepares a safe knowledge improvement draft.
Groups similar wording
“When will it arrive?” and “What is the delivery time?” become one clear topic.
Shows occurrence counts
Your team sees how many visitors were affected and can prioritise work by impact.
Prepares an editable draft
Unknown facts remain clearly marked. Quality Lab does not invent missing prices, dates, or conditions.
You publish only after review
An administrator adds verified data and turns the draft into a manual knowledge source ready for indexing.
AI regression testing
Every important change is tested
Build a library of questions the assistant must always handle. Quality Lab asks them through the current retrieval, knowledge base, and model—exactly like a real chat.
Expected answer
Semantically verifies that the new result preserves the confirmed meaning.
Required phrases
Checks critical information that the answer must contain.
Forbidden phrases
Detects claims or wording that must never be shown to customers.
Semantic consistency
Looks beyond identical words to meaning and possible contradictions.
Regression run
System instruction changed
Delivery times
Product returns
Product availability
Support contact
Quality Gate stopped the release
One critical scenario failed. The widget remains protected until a fix or conscious approval.
The result remains in history12 tests in total
Critical changes can protect the widget
When system instructions, the chat model, AI provider, or knowledge itself changes, a failed regression can temporarily pause answers. Customers will not see a known issue.
Blocking examples: changing the model, assistant instructions, embedding provider, or manual knowledge content.
Routine feed updates do not cause downtime
Regular price, stock, or product changes from an XML feed run a non-blocking check. The widget keeps answering while the administrator receives the result.
Non-blocking examples: scheduled Heureka, Google Merchant, or Informio XML synchronisation.
Where Quality Lab helps
For teams that do not want to assume quality
The same measurement works for product questions, customer support, public information, and internal know-how.
E-commerce
Discover questions about availability, compatibility, delivery, or returns that your product feed does not cover well enough.
Customer support
Learn which topics the assistant resolves independently and where a process must be added or the customer handed to a human.
Public services
Monitor answers about deadlines, forms, contacts, and processes where current information matters.
Internal knowledge
Verify that changing a policy or document did not degrade answers your team relies on.
Practical questions
How Quality Lab works in production
Measurement is part of the Informio administration and uses the same tenant isolation, AI connection, and security rules as the rest of the platform.
When is a conversation evaluated?+
After roughly ten minutes without a new message, the chat is considered complete and queued for evaluation. An administrator can also trigger it manually from the conversation detail.
Does Quality Lab consume AI tokens?+
AI evaluation and semantic comparison use the organisation's active AI connection, so they may consume provider tokens. Regression answers do not count towards your Informio response allowance.
Can Quality Lab disable my widget?+
Only when active tests exist and a blocking critical change fails regression. The administrator sees the exact reason and can fix the issue or consciously release the widget despite the result.
What if the AI provider is unavailable?+
Conversations receive a conservative rule-based fallback evaluation. A regression test requiring a real answer waits for a working AI connection.
Will this slow scheduled XML updates?+
No. Feed comparison remains deterministic and uses no AI. If semantic content changes, regression runs asynchronously and without blocking the widget.
Turn your know-how into an assistant that answers 24/7.
Start without a payment card or API key. Default Informio AI is ready automatically, while your own OpenAI account or AI server remains optional.
FREE plan · 100 answers · no payment card