Microsoft Web IQ: Audit Evidence Objects Before Trusting Benchmarks

Audit Web IQ source passages, ownership, support, freshness, duplication, context selection, latency, and failures without inheriting vendor benchmark claims.

Sonar sorts evidence objects through a gate, preserving one source-passage pair for a claim while rejects remain visible.

Direct answer: evaluate Microsoft Web IQ by preserving its evidence objects before a model turns them into an answer. Audit source ownership, canonical URL, passage support, freshness, duplication, context selection, latency, and failures as separate fields. Do not inherit Microsoft’s benchmark conclusions as if your application reproduced them.

Microsoft describes Web IQ as a grounding system for AI agents built on the Bing index. Its June 2026 material says the system returns passage-level structured evidence from web, news, image, and video sources. Microsoft also reports higher grounding satisfaction, sub-165 ms p95 latency, and about 2.5× speed versus its comparison cohort. Those are vendor-reported results under stated internal conditions, not a benchmark completed by Search Engine Answer.

Define the product and access state first

Microsoft’s announcement calls Web IQ a suite of AI-native grounding APIs, while its public page directs prospective users to express interest. Record the exact access path, contract, API surface, version, region, quota, and response schema available to your account. Do not build a test from a marketing diagram and assume undocumented fields exist.

Keep Web IQ separate from Bing consumer results, Bing Search APIs, Bing Webmaster Tools AI Performance, Copilot answers, Foundry IQ, and Work IQ. They may share infrastructure or naming, but their request contracts, metrics, and user outcomes are different.

Name the surface before interpreting an observation
SurfaceObserved objectUseful questionDo not infer
Web IQGrounding response and evidence objectsWhat evidence did the retrieval layer return?Consumer Bing rank or aggregate publisher visibility
Application contextSelected, ordered, truncated evidenceWhat reached the model?That every returned object was used
Generated answerClaims and citationsDid the answer remain inside the evidence?Retrieval quality from fluency alone
Vendor benchmarkMicrosoft chart and method noteWhat does Microsoft report?Your application’s quality or latency

Preserve the evidence object before transformation

Save the raw response or an approved redacted copy before reranking, deduplication, summarization, or prompt assembly. Assign stable run, query, and object IDs. Record the content type, displayed URL, resolved URL, canonical URL, publisher, dates, passage, structural metadata, and any score or confidence field the current schema exposes.

Hash the passage or raw record so later reviews can distinguish the retrieved object from a changed source page. If terms or data policy prevent storing full text, preserve the permitted identifiers, short verification excerpt, hash, retrieval time, and access restriction. Do not reconstruct a missing evidence object from the final answer.

Audit passage entailment, not keyword overlap

Split the generated answer into material claims. For each claim, ask whether the retrieved passage directly supports it, supports only part, supplies context, conflicts, or provides no identifiable support. Preserve scope, date, unit, population, geography, and uncertainty. A passage containing the same nouns can still fail to entail the claim.

Open the canonical source. Confirm that the passage exists in context and that the publisher closest to the fact owns the claim. Search snippets, syndicated copies, and copied press releases may be relevant, but they are not independent confirmation. Record inaccessible pages instead of accepting a title as evidence.

One label per claim-to-object relationship
LabelUse whenRequired note
Direct supportThe passage states the material propositionExact supporting span and preserved scope
Partial supportOnly part of a compound claim is supportedUnsupported words or missing qualification
ContextThe passage supplies background but not proofWhere factual support must come from
ContradictionThe passage conflicts with the claimTemporal, scoped, or substantive conflict
Duplicate contextThe object repeats another source owner or syndication clusterCanonical object ID and cluster
UnverifiableThe source or passage cannot be checkedAccess failure and evidence still needed

Separate retrieval, context, and generation

A strong evidence object can be omitted or truncated before generation. A weak answer can result from retrieval, context assembly, prompt instructions, the model, rendering, or citation placement. Preserve each layer so a failure has an owner.

  1. Retrieval: raw objects, order, filters, timestamps, errors, and zero-object results.
  2. Context assembly: selected object IDs, deduplication, ordering, character or token limits, and truncation.
  3. Generation: model and version, prompt, raw answer, rendered answer, citations, retries, and safety behavior.
  4. Evaluation: claim map, reviewer labels, disagreement, calculation, and final decision.

Do not calculate “citation accuracy” from only the successful answer rows. Include timeouts, errors, empty evidence sets, inaccessible sources, and invalid responses in the declared denominator.

Deduplicate by source owner and claim

Several passages from one page can improve coverage without creating independent corroboration. Several domains can reproduce one press release. Track object count, unique canonical pages, unique source owners, and syndication clusters separately.

Negative evidence also matters. Record an authoritative current source that the system did not retrieve, a decisive limitation missing from an otherwise relevant passage, or a canonical mismatch. Retrieval recall cannot be estimated from returned objects alone; it needs a declared reference set for the query.

Treat multimodal evidence as more than a thumbnail

For image and video objects, verify the landing page, media owner, surrounding text, publication date, and whether the returned passage describes the media or only nearby copy. A thumbnail does not prove what appears in the full media. Record unavailable transcripts, changed captions, region restrictions, and rights boundaries.

If the application extracts facts from a chart or frame, keep that extraction as a separate observation with its method and reviewer. Do not present a conceptual image, generated caption, or nearby article text as direct evidence from the media itself.

Reproduce vendor benchmarks only with a declared contract

Microsoft reports grounding satisfaction on 3,000 global, blind queries sampled from production with configurations including 10 results and 10,000 characters per result. It also reports sub-165 ms p95 latency and roughly 2.5× faster performance than the next alternative in its cohort, measured from virtual machines in five data-center regions with unique queries to avoid cache hits.

Those details improve attribution but do not expose the complete query set, competitor identities, scoring rubric, traffic mix, failure treatment, or every environment control. The safe wording is “Microsoft reports.” A reproduction needs its own sample, geography, account tier, API version, network location, concurrency, cache rule, timeout, retry policy, comparator configuration, and reviewer rubric.

Publish components before any weighted total
MeasureNumeratorDenominatorBoundary
Claim coverageMaterial claims with at least one objectAll material claimsPresence is not entailment
Direct supportClaims directly supported after reviewClaims evaluatedReviewer judgment needs a passage
Primary-source rateDirectly supported claims using closest ownerDirectly supported claimsNot every question has an official source
Freshness passObjects meeting a predefined date ruleObjects where freshness mattersRule must be set before review
ReliabilityComplete valid responsesAll attempted requestsKeep timeouts and empty sets
LatencyMeasured distributionAll declared attemptsReport median, p95, and failures

Download the evidence-object scorecard

The CSV below joins the raw object, resolved source, passage hash, claim relationship, source ownership, freshness rule, context-selection state, answer use, latency, error, reviewers, and limitation. Its sample rows begin with EXAMPLE-REMOVE; delete them before adding a real run.

Download the Microsoft Web IQ evidence-object scorecard (CSV)

Keep raw response files beside the scorecard under an access policy appropriate to the content. The citation absorption audit provides compatible claim-to-passage labels, and the tool-score guide helps expose weights instead of hiding them in one number.

Release gates for an evaluation

  • The exact Web IQ product surface, access state, version, region, and date are recorded.
  • Every published percentage has a numerator, denominator, and missing-data rule.
  • Vendor claims are attributed and visually separated from reproduced results.
  • Raw evidence objects and selected context can be reconstructed without credentials in the public artifact.
  • Zero-object responses, errors, timeouts, and inaccessible sources remain in scope.
  • Two reviewers adjudicate ambiguous support labels or the report states that only one reviewer was used.
  • No evidence object, citation, or latency result is converted into a consumer search-ranking claim.

Limits and re-audit triggers

Search Engine Answer has not received or run a Web IQ account for this article and has not reproduced Microsoft’s benchmark. Public documentation may not expose the response schema available to a particular customer. The method therefore defines the evidence required for a pilot; it does not certify product quality.

Start a new run when access terms, API version, region, retrieval configuration, evidence schema, passage size, query set, comparator, model, context limit, scoring guide, or source corpus changes. Preserve prior runs as dated observations. Web content can change after retrieval, so retain the canonical URL, retrieved passage or permitted hash, and review time together.

Primary sources

Source check: August 31, 2026. Reconfirm access, schema, benchmark wording, and product boundaries before every evaluation.

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