HEALTH A reasoning model hit 88.6% diagnostic accuracy on clinicopathological cases. In the same window, a five-hosp…+ HEALTH A reasoning model reached 88.6% exact or near-exact accuracy on clinicopathological cases.+ EDUCATION Small-scale district pilots report gains for students who previously had no outside tutoring access. POLICY Post-market monitoring standards for clinical AI tools remain unsettled as clearances accelerate. LABOR The labor market's two truths: large projected role creation and concentrated, measurable displacement. LABOR Employment for coders aged 22–25 has fallen roughly 20% against its late-2022 peak.+ LABOR New AI-adjacent skills already carry wage premiums in 1 of every 10 job postings in advanced economies. LABOR Current estimates vary 5x depending on methodology.
Sunday, July 12, 2026
TruvaceThe trace, not the pitch
The Index

What the evidence says. What the public feels.

The Sourced Indexranks AI’s measured gains and problems on verified evidence. The Public Pulse tracks what readers report, register, and debate. The Impact Ranking tracks which AI companies carry the largest visible public footprint.

Prototype data — sample ranking under a methodology draft. These are editorial placeholder readings, not measured scores.

This ranks visible public footprint— evidence-weighted company visibility — never “best,” “safest,” or “most powerful.” A company can carry documented gains and documented problems at once and still be the most consequential public footprint in AI.

  1. 01
    OpenAI logo

    OpenAI

    Stable

    Maker of ChatGPT and the GPT model line; the most publicly visible consumer and developer AI surface.

    94 visible impact · Dominant public footprintprototypeAccountability risk: HighEvidence confidence: High6 signal sources · updated 2026-07-12

    Why this rank changed: Held rank: consumer reach and developer adoption remain the largest visible AI surface; ongoing litigation and governance coverage keep public attention elevated.

    What we don’t know: True enterprise revenue mix, internal safety-incident base rates, and private usage volumes are not publicly visible.

    OpenAlex — research citing OpenAI models · Wikipedia pageview signal · CourtListener docket search

  2. 02
    Nvidia logo

    Nvidia

    Rising

    The compute layer under nearly all frontier AI; GPU supply and pricing shape the entire sector.

    91 visible impact · Infrastructure-wide footprintprototypeAccountability risk: ModerateEvidence confidence: High5 signal sources · updated 2026-07-12

    Why this rank changed: Rose on sustained datacenter demand visible in public filings and the breadth of sectors dependent on its hardware.

    What we don’t know: Allocation priorities between customers and real utilization rates of shipped compute are not disclosed.

    SEC EDGAR filings · Wikipedia pageview signal

  3. 03
    Google DeepMind logo

    Google DeepMind

    Stable

    Google's consolidated AI research and product arm: Gemini, AlphaFold, and search-scale deployment.

    88 visible impact · Search-scale footprintprototypeAccountability risk: ElevatedEvidence confidence: High6 signal sources · updated 2026-07-12

    Why this rank changed: Held rank: distribution through Search, Android, and Workspace keeps observable reach enormous; peer-reviewed output (AlphaFold line) is the strongest sourced-gain record in the set.

    What we don’t know: How much Gemini usage is organic versus bundled distribution is not separable from public data.

    OpenAlex — DeepMind publications · Alphabet SEC filings

  4. 04
    Microsoft AI logo

    Microsoft AI

    Stable

    Copilot across Windows, Office, and Azure; the widest enterprise distribution channel for AI.

    85 visible impact · Enterprise-wide footprintprototypeAccountability risk: ModerateEvidence confidence: High5 signal sources · updated 2026-07-12

    Why this rank changed: Held rank: Copilot seat counts surface in filings and the Azure–OpenAI dependency keeps Microsoft inside most enterprise AI deployments.

    What we don’t know: Active-use rates behind enterprise seat licenses are not publicly verifiable.

    SEC EDGAR filings · GitHub — Copilot ecosystem

  5. 05
    Meta AI logo

    Meta AI

    Rising

    Llama open-weight models plus AI features across Facebook, Instagram, and WhatsApp's billions of users.

    79 visible impact · Platform-scale footprintprototypeAccountability risk: HighEvidence confidence: Moderate4 signal sources · updated 2026-07-12

    Why this rank changed: Rose on open-weight adoption breadth (visible in public model downloads and derivative work) and assistant rollout across its apps.

    What we don’t know: Engagement quality of in-app AI features and downstream uses of open weights are hard to observe.

    GitHub — Llama ecosystem · SEC EDGAR filings

  6. 06
    Anthropic logo

    Anthropic

    Rising

    Maker of the Claude model family; enterprise and developer adoption with a safety-forward public posture.

    76 visible impact · Fast-compounding footprintprototypeAccountability risk: ModerateEvidence confidence: Moderate4 signal sources · updated 2026-07-12

    Why this rank changed: Rose on visible enterprise integrations and developer-tool adoption; public research output keeps attention high relative to size.

    What we don’t know: Private usage volumes and revenue composition are not publicly disclosed.

    OpenAlex — research citing Claude/Anthropic · Wikipedia pageview signal

  7. 07
    xAI logo

    xAI

    Rising

    Grok models distributed through X; compute buildout and platform integration drive its visibility.

    62 visible impact · Platform-tied footprintprototypeAccountability risk: ElevatedEvidence confidence: Emerging3 signal sources · updated 2026-07-12

    Why this rank changed: Rose on publicly visible compute expansion and distribution through X; independent usage evidence remains thin.

    What we don’t know: Usage outside the X platform and enterprise traction are largely unverifiable from public signals.

    Wikipedia pageview signal

  8. 08
    Perplexity logo

    Perplexity

    Rising

    AI-native answer engine; a visible challenger to traditional search with publisher-relations friction.

    55 visible impact · Consumer-niche footprintprototypeAccountability risk: ElevatedEvidence confidence: Emerging3 signal sources · updated 2026-07-12

    Why this rank changed: Rose on sustained press attention and publisher disputes that made its crawling and citation practices publicly observable.

    What we don’t know: Retention and query volumes are private; footprint reading leans on attention signals.

    Wikipedia pageview signal

  9. 09
    Mistral AI logo

    Mistral AI

    Stable

    European open-weight model lab; the reference point in EU AI policy and sovereignty debates.

    49 visible impact · Regional-anchor footprintprototypeAccountability risk: LowEvidence confidence: Emerging3 signal sources · updated 2026-07-12

    Why this rank changed: Held rank: open-weight releases keep developer visibility steady; policy prominence in the EU outweighs modest consumer reach.

    What we don’t know: Commercial deployment scale behind European enterprise deals is not publicly visible.

    GitHub — Mistral releases · Wikipedia pageview signal

  10. 10
    Cohere logo

    Cohere

    Newly added

    Enterprise-focused model provider; lower consumer visibility, meaningful business-tooling presence.

    41 visible impact · Enterprise-quiet footprintprototypeAccountability risk: LowEvidence confidence: Emerging2 signal sources · updated 2026-07-12

    Why this rank changed: Newly added to the prototype set to represent enterprise-first vendors whose footprint is real but publicly quiet.

    What we don’t know: Most of its deployment surface is behind enterprise contracts and invisible to public signals — the clearest example of why footprint ≠ importance.

    GitHub — Cohere SDKs

How this ranking works (and what it is not)

The tracker ranks visible public footprint using adoption signals, public attention, sourced gains, sourced harms, regulatory pressure, and transparency. It is not a ranking of the “best” AI company. Evidence-backed problems do not subtract from footprint: consequence counts in both directions, and accountability risk is shown as its own reading.

ComponentWeightSignals
Adoption / Reach25%usage, integrations, distribution surfaces
Public Attention20%news volume, pageviews, search interest
Evidence-Backed Gains20%sourced positive impact tied to the company
Evidence-Backed Problems20%sourced harms, litigation, regulatory action — consequence raises footprint, it does not subtract
Transparency / Accountability15%disclosures, model cards, incident reporting, filings

Honest limits: public signals are incomplete — private usage, revenue, and safety data may not be visible. Company self-claims are discounted unless independently supported. Every reading carries its source count, last-updated date, and a confidence label. Until the server-side measurement pipeline ships (public sources only, fetched server-side against an allowlist, rate-limited, human-certified before publication), every number on this page is prototype data and labeled as such.

Recomputed live from the record · Jul 12, 2026, 10:57 AM