AI Trust Startup Funding
In our updated market reports, you will find everything you need
SUMMARY
This report analyzes publicly disclosed equity rounds raised by pure-play AI trust companies between August 2024 and July 2026. We only kept rounds of $300K or more, excluded debt, grants, acquisitions, broad cybersecurity companies, and non-pure-play AI companies, and built a final sample of 24 disclosed deals across 22 unique companies.
Over this period, the AI trust market raised $906.1M across 24 disclosed equity rounds. Deal activity averaged exactly 1.0 disclosed round per month.
The AI trust market is active, but not yet huge by frontier AI standards. The median round size is $32.05M, and there are no disclosed rounds above $100M.
Capital is moderately concentrated. The top deal represents 11.04% of all capital, the top 3 deals represent 27.59%, and the top 10 deals represent 70.52%.
AI Security Tools dominate the AI trust market. They account for 14 of 24 deals and $556M raised, or 61.36% of all disclosed capital.
Model Monitoring Systems have the strongest capital share to deal share ratio. Only 2 deals raised $150M, showing that production AI observability can command large checks.
The market is balanced between formation and scale-up. Seed and Series A rounds represent 49.33% of capital, while Series B and Series C rounds represent 48.24%.
North America is the clear center of gravity. It captured 18 of 24 deals and $730.1M, equal to 80.58% of disclosed capital.
The Middle East is the second-largest region, driven mainly by Israeli AI security companies. It captured 5 deals and $169M, or 18.65% of total capital.
Repeat investors cluster around security, infrastructure, and observability. Evolution Equity Partners, Datadog, Samsung, Lightspeed, a16z, Greylock, M12, Menlo Ventures, Mayfield, and Bain Capital Ventures each appeared more than once.
What are all the funding deals in the AI trust market from August 2024 to July 2026?
The table below lists every disclosed equity round raised by pure-play AI trust companies between August 2024 and July 2026. We count as “pure-play” AI trust companies those focused on software and services that make AI systems safer, more reliable, more explainable, and more compliant.
Each row shows the company, what it does, its category, the deal date, the funding stage, the round size, the region, the main investors when available in the dataset, and the announcement source.
| Company | What they do | Category | Date | Stage | Deal size | Region | Main investors | Source |
|---|---|---|---|---|---|---|---|---|
| Protect AI | AI and machine-learning security platform for AI security posture, model security, LLM security, and AI supply-chain risks | AI Security Tools | Aug 2024 | Series B | $60M | North America | Evolution Equity Partners; Samsung Ventures | BusinessWire |
| Braintrust | Evaluation, experimentation, tracing, and observability infrastructure for AI applications and agents | Model Evaluation Tools | Oct 2024 | Series A | $36M | North America | a16z; Greylock; Elad Gil; Basecase Capital | Braintrust |
| Relyance AI | AI-powered data governance and compliance platform for controlling data use and supporting compliant AI adoption | AI Compliance Platforms | Oct 2024 | Series B | $32.1M | North America | M12; Menlo Ventures | TechCrunch |
| Galileo | Generative AI evaluation and observability platform for enterprise AI teams | Model Evaluation Tools | Oct 2024 | Series B | $45M | North America | Not specified in dataset | PR Newswire |
| Noma Security | AI application security platform securing the data and AI lifecycle from development to production | AI Security Tools | Oct 2024 | Series A | $32M | Middle East | Evolution Equity Partners; Glilot Capital Partners | FinTech Global |
| Prompt Security | Generative AI security platform protecting enterprises from AI application, employee, and data risks | AI Security Tools | Nov 2024 | Series A | $18M | Middle East | Not specified in dataset | Prompt Security |
| Arize AI | AI observability and LLM evaluation platform for monitoring, troubleshooting, and improving AI systems in production | Model Monitoring Systems | Feb 2025 | Series C | $70M | North America | Datadog; M12 | PR Newswire |
| Knostic | AI security platform focused on need-to-know access controls that prevent sensitive enterprise data leakage through LLMs | AI Security Tools | Mar 2025 | Seed | $11M | Middle East | Not specified in dataset | Calcalist |
| SplxAI | Offensive AI security and automated red teaming platform for AI agents and LLM applications | Red Teaming Services | Mar 2025 | Seed | $7M | Europe | Not specified in dataset | SplxAI |
| Straiker | AI-native security platform for protecting enterprise AI applications and autonomous agents | AI Security Tools | Mar 2025 | Seed | $21M | North America | Lightspeed Venture Partners; Bain Capital Ventures | SecurityWeek |
| Aurascape | AI-native security platform providing visibility, protection, and automated governance for enterprise AI usage | AI Security Tools | Apr 2025 | Series A | $50M | North America | Menlo Ventures; Mayfield | Aurascape |
| Virtue AI | AI security platform helping enterprises secure, evaluate, and govern AI deployments | AI Security Tools | Apr 2025 | Series A | $30M | North America | Lightspeed Venture Partners | BusinessWire |
| Pillar Security | AI detection and response platform for securing AI-driven software systems and AI agents | AI Security Tools | Apr 2025 | Seed | $9M | North America | Not specified in dataset | Pillar Security |
| EQTY Lab | Verifiable AI governance and AI integrity platform using provenance, policy enforcement, and runtime assurance | AI Governance Platforms | May 2025 | Unknown | $5M | North America | Not specified in dataset | CB Insights |
| Hirundo | Machine unlearning platform that helps AI models forget problematic data, hallucinations, bias, and vulnerabilities | Bias Detection Software | Jun 2025 | Seed | $8M | Middle East | Not specified in dataset | PR Newswire |
| Prophet Security | Agentic AI SOC platform automating detection engineering, investigations, threat hunting, and incident response | AI Security Tools | Jul 2025 | Series A | $30M | North America | Bain Capital Ventures | BusinessWire |
| Noma Security | Unified AI and agent security platform securing AI systems from development through production | AI Security Tools | Jul 2025 | Series B | $100M | Middle East | Evolution Equity Partners; Glilot Capital Partners | PR Newswire |
| Runlayer | Security platform for Model Context Protocol deployments, with visibility and controls over AI-agent connections to tools and data | AI Security Tools | Nov 2025 | Seed | $11M | North America | Not specified in dataset | Runlayer |
| Vijil | AI agent trust and resilience platform for testing, securing, and improving enterprise AI agents | Model Evaluation Tools | Nov 2025 | Unknown | $17M | North America | Mayfield | FinSMEs |
| WitnessAI | AI security and governance platform for enterprise AI use, AI applications, and AI agents | AI Security Tools | Jan 2026 | Series A | $58M | North America | Samsung Ventures | PR Newswire |
| Braintrust | Production AI observability layer for evaluating, tracing, and monitoring AI applications and agents | Model Monitoring Systems | Feb 2026 | Series B | $80M | North America | a16z; Greylock; Elad Gil; Basecase Capital; Datadog | Braintrust |
| Arcade.dev | Secure action layer for production AI agents, controlling how AI agents connect to tools and take actions | AI Security Tools | Jun 2026 | Series A | $60M | North America | Not specified in dataset | BusinessWire |
| NewCore AI | Security-first identity platform rebuilt for enterprises managing both human workers and AI agents | AI Security Tools | Jun 2026 | Seed | $66M | North America | Evolution Equity Partners | NewCore |
| Patronus AI | AI evaluation and simulation platform for stress-testing AI agents and improving AI systems before production use | Model Evaluation Tools | Jun 2026 | Series B | $50M | North America | Datadog; Samsung Ventures; Lightspeed Venture Partners | TMCnet |
OUR METHODOLOGY TO BUILD THIS TRACKER
We built this AI trust funding tracker by reviewing every publicly disclosed equity round raised by pure-play AI trust companies between August 2024 and July 2026. A company counts as pure-play when more than 80% of its activity is dedicated to AI safety, AI reliability, AI governance, AI security, AI monitoring, AI evaluation, AI compliance, bias detection, explainability, or red teaming.
We applied four filters to build the dataset. First, we only included equity rounds, so debt, grants, acquisitions, and non-dilutive awards are excluded. Second, we only counted rounds of $300K or more. Third, we only kept pure-play AI trust companies. And fourth, every entry had to be confirmed by a direct company announcement, a press release, or a tier-1 media report, with the source URL preserved for every row.
The final dataset contains 24 disclosed deals across 22 unique companies, and every average, median, share, and concentration ratio is computed on that disclosed sample. Privately raised rounds that were never publicly announced are necessarily missing, which is a known limitation of any public-only AI trust funding tracker.
How active has fundraising been in the AI trust market?
As of July 2026, fundraising in the AI trust market has been steady but selective. Over the past 24 months, companies raised 24 disclosed equity rounds and $906.1M combined, equal to one disclosed deal per month.
The AI trust market is not a high-volume startup category yet. The dataset includes only 22 unique companies, which means visible venture activity is concentrated around a limited set of pure-play vendors.
Monthly deal flow looks stable, but monthly capital is uneven. The average raised per month is $37.75M, while the median is only $6.5M, showing that a few large months drive the headline total.
The funding base is meaningful without becoming overheated. The median round is $32.05M and the average round is $37.75M, so most visible deals are institutional enterprise software rounds rather than small experiments.
How concentrated has fundraising been in the AI trust market?
As of July 2026, fundraising in the AI trust market is concentrated, but not completely dependent on one round. Over the past 24 months, the top deal represents 11.04% of total capital, while the top 3 deals represent 27.59%.
The top 5 deals account for 41.50% of all disclosed capital in the AI trust market. The top 10 deals account for 70.52%, which means most dollars still sit in a small group of perceived infrastructure winners.
This concentration is meaningful, but it is less extreme than in markets driven by billion-dollar frontier-model rounds. The largest AI trust round is $100M, and no company raised more than that in a single disclosed round.
The right reading is that the AI trust market has many serious checks, but only a few category-defining checks. Investors are spreading money across the stack, then doubling down on the companies closest to deployment control.
How much of the AI trust funding signal is driven by outliers?
As of July 2026, the AI trust funding signal is influenced by outliers, but not dominated by billion-dollar anomalies. Over the past 24 months, 9 of 24 disclosed rounds were $50M or larger.
There are 7 megarounds above $50M, representing 29.17% of total deals. At the same time, there are no rounds above $100M, which sets a clear ceiling on the current market.
The largest rounds include Noma Security at $100M, Braintrust at $80M, Arize AI at $70M, NewCore AI at $66M, Protect AI at $60M, Arcade.dev at $60M, and WitnessAI at $58M. These deals show where investors see platform potential.
The market’s outlier dependency should be read carefully. Removing rounds above $50M leaves $412.1M in disclosed capital, so the AI trust market still has a real mid-market base.
Is the AI trust market broad with many targets, or narrow with few fundable companies?
As of July 2026, the AI trust market is narrow rather than broad. Over the past 24 months, only 22 unique companies produced 24 disclosed equity rounds that met the scope and size filters.
The small gap between deals and unique companies means repeat fundraising exists, but it does not fully dominate the dataset. Braintrust and Noma Security each raised twice, while most companies appeared only once.
The category mix also shows a narrow market. AI Security Tools alone account for 14 of 24 deals, while every other category has four deals or fewer.
This means the AI trust market is not yet a broad landscape of many equally fundable subcategories. It is mostly an AI security market, with evaluation, monitoring, compliance, governance, red teaming, and bias tools forming smaller adjacent lanes.
Is AI trust mostly an early-stage formation market or a late-stage scaling market?
As of July 2026, the AI trust market is balanced between early-stage formation and scale-up. Over the past 24 months, Seed and Series A rounds raised $447M, while Series B and Series C rounds raised $437.1M.
Early-stage capital represents 49.33% of disclosed dollars in the AI trust market. That is unusually strong for an enterprise software category where buyers often wait for mature vendors.
Late-stage capital represents 48.24% of disclosed dollars, so the market is also not purely experimental. The presence of Series B and Series C rounds shows that some companies are already scaling into production infrastructure roles.
Seed rounds are frequent but smaller. The Seed category has 7 deals and $133M raised, with a median round size of $11M, which suggests investors want sharp technical wedges rather than broad early narratives.
Which categories attract the most investor attention in AI trust?
As of July 2026, AI Security Tools attract the most investor attention in the AI trust market. Over the past 24 months, the category captured 14 of 24 deals and $556M, equal to 61.36% of disclosed capital.
This is the clearest signal in the dataset. Investors are treating AI trust mainly as a security-control problem, not mainly as an ethics, explainability, or policy problem.
Model Evaluation Tools rank second by deal count with 4 deals and $148M raised. Model Monitoring Systems rank second by capital intensity, with only 2 deals but $150M raised.
The long tail is much smaller. AI Compliance Platforms raised $32.1M, Bias Detection Software raised $8M, Red Teaming Services raised $7M, and AI Governance Platforms raised $5M.
Which categories attract disproportionately large checks in the AI trust market?
As of July 2026, Model Monitoring Systems attract disproportionately large checks in the AI trust market. Over the past 24 months, the category had only 2 deals but raised $150M, giving it the highest capital share to deal share ratio at 1.99.
The average Model Monitoring Systems round is $75M, which is the highest category average in the dataset. Arize AI and Braintrust show that production observability can become a core infrastructure budget.
AI Security Tools are large because they are frequent, not because every check is oversized. Their average deal size is $39.71M, close to the overall market average of $37.75M.
Model Evaluation Tools also sit near parity, with an average of $37M and a capital share to deal share ratio of 0.98. Evaluation matters, but the largest checks come when evaluation connects to production monitoring, security, or agent control.
Which geographies matter most for fundraising in the AI trust market?
As of July 2026, North America matters most for fundraising in the AI trust market. Over the past 24 months, it captured 18 of 24 deals and $730.1M, equal to 80.58% of disclosed capital.
North America leads on both volume and check size. The region’s average round is $40.56M and its median round is $40.5M, showing a deep base of enterprise software financing.
The Middle East ranks second, with 5 deals and $169M raised. This activity is largely tied to Israeli AI security companies, where the product looks close to cybersecurity infrastructure.
Europe is barely visible in the disclosed dataset. It has only 1 deal and $7M raised, despite Europe’s strong regulatory role in AI governance and compliance.
Is the AI trust opportunity set broad or concentrated in one hub?
As of July 2026, the AI trust opportunity set is highly concentrated in North America, with a secondary Middle East cluster. Over the past 24 months, those two regions together captured 99.23% of disclosed capital.
North America alone accounts for 75% of disclosed deals and 80.58% of dollars. That makes the AI trust market mainly a US enterprise software and infrastructure funding story.
The Middle East accounts for 20.83% of deals and 18.65% of dollars. The region’s strength comes from AI security companies, not from broad standalone AI governance or explainability platforms.
Asia-Pacific, Latin America, and Africa do not appear in the disclosed dataset. That does not mean those regions lack AI trust needs, but it does mean venture-backed pure-player formation is currently concentrated elsewhere.
Is AI trust a market of small experiments or scaled financings?
As of July 2026, AI trust is closer to a scaled enterprise software financing market than a small experiment market. Over the past 24 months, the median disclosed round was $32.05M.
No deal in the dataset was below $5M. The smallest visible rounds still look like institutional venture rounds, including EQTY Lab at $5M, SplxAI at $7M, and Hirundo at $8M.
The middle of the market is healthy. There are 8 deals between $5M and $20M, 7 deals between $20M and $50M, and 9 deals at $50M or more.
The absence of rounds above $100M matters. Investors are funding AI trust aggressively, but they are not underwriting it like foundation-model labs or capital-intensive AI infrastructure buildouts.
Who are the investors that appear the most in AI trust fundraising?
As of July 2026, repeat investors in the AI trust market are mostly security, infrastructure, and AI platform specialists. Over the past 24 months, several investors appeared in more than one disclosed deal.
Evolution Equity Partners, Datadog, Samsung or Samsung Ventures, and Lightspeed Venture Partners each appear in 3 deals. That is the strongest repeat-investor signal in the dataset.
a16z, Greylock, Elad Gil, and Basecase Capital each appear in both Braintrust rounds. M12 appears in Relyance AI and Arize AI, while Menlo Ventures appears in Relyance AI and Aurascape.
Mayfield appears in Aurascape and Vijil, and Bain Capital Ventures appears in Straiker and Prophet Security. These repeat patterns suggest investors are backing companies that operationalize AI trust inside security, observability, and agent workflows.
One important caveat is that round announcements rarely disclose individual investor check sizes. Investor counts should be read as participation signals, not as exact capital allocation by investor.
INSIGHTS
The insights below come from reviewing every disclosed equity round in the AI trust market between August 2024 and July 2026. They are not row-by-row summaries. They are the reusable patterns that kept showing up across the 24-deal dataset, and they are meant to stay useful when reading future AI trust funding announcements.
- AI security has become the carrier category for AI trust. The category holds 58.33% of deals and 61.36% of capital, which means investors are funding practical control layers ahead of abstract trust narratives.
- The AI trust market is not evenly distributed across the stack. Runtime defense, agent security, identity, data leakage, and AI application security repeatedly attract larger rounds than standalone governance or explainability tools.
- Governance is increasingly embedded inside security, monitoring, and compliance platforms. Standalone AI governance has only one small disclosed deal in the dataset, which suggests the budget owner is shifting toward operational teams.
- Model monitoring has the strongest capital intensity signal in the AI trust market. Only 2 deals produced $150M, which shows that trusted AI becomes more valuable when it sits inside production infrastructure.
- The market is moving from pre-deployment evaluation toward production control. Braintrust, Arize AI, WitnessAI, Runlayer, Arcade.dev, NewCore AI, and Noma Security all point toward runtime, identity, workflow, and action layers.
- The top 10 deals represent 70.52% of all disclosed capital. That means fundraising credibility is highly concentrated, even though the market has no billion-dollar outlier.
- The median round is $32.05M and the average is $37.75M. This is a moderately skewed enterprise software market, not a frontier-model financing market.
- The lack of rounds above $100M is important. AI trust is attracting serious capital, but investors are still applying enterprise software discipline rather than foundation-model financing logic.
- The $50M to $100M range is the current validation ceiling. Noma Security, Braintrust, Arize AI, NewCore AI, Protect AI, Arcade.dev, and WitnessAI define where investors see platform potential.
- Early-stage and late-stage capital are nearly balanced. This implies the AI trust market is neither purely experimental nor fully mature, but moving from formation into scale-up.
- Seed rounds need a very specific wedge to stand out. MCP security, agent identity, machine unlearning, AI SOC automation, and agent red teaming are more compelling than generic trust claims.
- The strongest investor signal comes from cyber and infrastructure specialists. Evolution Equity Partners, Lightspeed, Bain Capital Ventures, Mayfield, Menlo Ventures, and Datadog repeatedly appear around operational AI trust companies.
- North America remains the center of gravity for AI trust fundraising. The region captures 80.58% of disclosed capital, showing that US enterprise software buying still anchors the category.
- Israel is structurally strong where AI trust looks like cybersecurity. Middle East rounds represent only 20.83% of deals, but they still capture 18.65% of capital.
- Europe is nearly absent in disclosed equity capital, despite its regulatory role. Regulation does not automatically translate into venture-backed category leadership.
- Compliance-only narratives appear less investable than security-first narratives. AI compliance companies likely need a data-control, monitoring, or security wedge to command larger checks.
- The repeated language around agent security, MCP, action layers, identity, and AI SOC shows how fast the market has moved. Investors are preparing for autonomous agents touching real enterprise systems.
- Pure model evaluation remains important, but it is being pulled toward continuous simulation and production observability. Evaluation becomes more valuable when it can shape real deployment decisions.
- The strongest rounds are tied to environments of proof. Companies that can test, monitor, block, govern, or enforce AI behavior inside workflows raise more than companies selling policy frameworks alone.
- Explainability looks more like a feature than a standalone venture category. The dataset contains no meaningful disclosed funding for pure explainability companies, which suggests buyers value measurable control more than interpretability alone.
- Bias detection also appears undercapitalized as a standalone category. Hirundo’s round suggests bias reduction attracts capital when tied to technical remediation, not just measurement.
- Red teaming is present but undercapitalized. It may be viewed as a service or feature unless paired with continuous defense, automated remediation, or production security controls.
- The most defensible AI trust startups are likely to become systems of record for AI behavior. Monitoring traces, evaluation datasets, identity events, policy decisions, and agent actions are durable control points.
BusinessWire (Protect AI), Braintrust (Series A), TechCrunch (Relyance AI), PR Newswire (Galileo), Prompt Security (Series A), PR Newswire (Arize AI), Calcalist (Knostic), SplxAI (Seed), SecurityWeek (Straiker), Aurascape (Series A), BusinessWire (Virtue AI), Pillar Security (Seed), PR Newswire (Hirundo), BusinessWire (Prophet Security), PR Newswire (Noma Security), Runlayer (Seed), FinSMEs (Vijil), PR Newswire (WitnessAI), Braintrust (Series B), BusinessWire (Arcade.dev)
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- Which companies have raised the most funding in the AI trust market?
- Which companies are the most valued in the AI trust market?
