Tokio Marine North America Services Selects Monitaur for Enterprise AI Governance

ThinkingAI, which builds autonomous growth software for consumer and gaming companies, has opened its analytics, engagement and agent stack to game studios that buy software with a card instead of a procurement cycle, offering four self-serve plans priced from $0 to $999 a month. The Free tier costs $0 and includes 2 million events a month, 1 project, 1 seat, 12 months of data retention and $10 in Agent Credits for the first month, with no credit card required. Starter costs $199 a month for 5 million events, 2 projects, 5 seats, 24 months of retention and $25 a month in Agent Credits, while Pro costs $399 a month for 10 million events, 2 projects, 10 seats, 48 months of retention and $50 a month in Agent Credits. Team costs $999 a month for 30 million events, 3 projects, 15 seats, 60 months of retention and $100 a month in Agent Credits, and an Enterprise tier is sold by agreement with sales for larger studios with compliance or data residency requirements. Annual billing saves 20%, paid plans are billed through Stripe and can be cancelled at any time, and a studio that outgrows its event allowance moves up a plan inside the product with no re-instrumentation and no migration. The plans follow ThinkingAI's Sept. 16 launch of the Agentic Engine and draw on 10 years of behavioral data across more than 1,500 enterprises and 8,000 applications, including Sega, Krafton, Habby, Century Games, Xiaomi, Yostar, TCL and FunPlus, and are being announced at the ThinkingAI Agentic Game Growth Summit in Istanbul, co-hosted with Mobidictum.

Atlassian Corporation announced the launch of its Forward Deployed Engineering program, which embeds senior applied AI engineers directly into customer environments to deploy production-ready AI solutions. The program targets a gap between AI adoption and business impact: while 85% of knowledge workers use AI, only 6% of executives can point to clear, organization-wide ROI, according to Atlassian's report Leading with Context: Lessons from Atlassian's AI Journey. Avani Prabhakar, Chief People and AI Enablement Officer at Atlassian, said the company is seeing 50% higher AI adoption in engaged accounts as a result of embedding engineers with customers. In Atlassian testing, grounding AI agents in the Teamwork Graph produced answers that were 44% higher quality while using 48% fewer tokens. Expedia used the program to archive 600,000 pages across Confluence and save approximately 3,200 hours annually, with engineering teams now running 10,000+ agent invocations each month across 50 live projects, while Reddit is partnering with the engineers to accelerate its enterprise AI transformation. Engagements typically run 12 weeks, and Atlassian is also releasing The Atlassian Forward Deployed Engineering Playbook.

Atlassian announced AMP: The Agentic Multiplayer Protocol at its Team '26 Europe conference, a new protocol that lets AI agents work alongside human teams in the flow of work. AMP gives agents context, identity, and governance, allowing them to participate through @mentions in Confluence, Jira comment threads, or Loom video briefs, while the Atlassian MCP Server pulls in context from third-party tools like Figma or IDEs. Every agent under AMP has a clear owner and distinct profile, appearing in real-time presence bars and cursors alongside human teammates, and agents are grounded in the Teamwork Graph, which now connects more than 250 billion objects and relationships. Atlassian also introduced a new Atlassian MCP Server, which now has nearly 2 million monthly active users and handles over 15 million daily tool calls, a 15x jump in six months, using up to 25% fewer tokens for the same Jira and Confluence work in internal benchmarking on Claude models. The company said it has shipped over 120 enterprise capabilities during the last year, with people and agents now working together more than 10 million times a month, and announced new capabilities including Agent Sessions, Non-Human Identities, Record for Agent, and Interactive PR Reviews.

ServiceNow President and COO Amit Zavery said the company remains bullish on enterprise AI demand and continues to beat and raise all its financial metrics. Speaking with Haslinda Amin on the sidelines of Token2049 in Singapore, Zavery said ServiceNow's growth rates have accelerated and that its AI-native product portfolio, including AI Control Tower, AI Workflow Factory, Autonomous Engineer and the recently launched Flow, is driving adoption. He dismissed concerns that customers are insourcing software, saying building software is usually just 20% of the cost of running and operating enterprise software, and that large language models account for less than 8 to 10% of ServiceNow's technology stack. Zavery said recent acquisitions, including Armis and Vectra, have made ServiceNow the eighth largest cyber security vendor in the world and augment rather than mask its core business, which he described as very strong. He said the company's plan to reach $30 plus billion dollars in the next three years remains on track, and that ServiceNow will stay product-led while continuing to look at acquisitions that extend its capabilities.

Ampersand announced a $15 million Series A led by Bessemer Venture Partners, with participation from existing investors Matrix and Flex Capital, to build integration infrastructure that lets agentic applications read and write inside legacy systems of record such as CRM and ERP platforms. New investors in the round include Yelp, Tenacity Capital, CTO Fund, Mana Ventures, and prominent angel investors, and Bessemer Partner Lauri Moore will join Ampersand's board. The company also announced the beta release of Andi, its AI integration agent that helps developers with the implementation work required to run their products in each customer's environment. Ampersand was founded by Ayan Barua, formerly CTO and co-founder of Siftery and VP of Engineering at G2, and Lauren Long, who built Firebase Extensions at Google; the two spoke with more than 100 companies building integrations before writing Ampersand's first line of code. Moore said connecting an agent to a system of record is a demo, but keeping that connection alive across hundreds of customers, with writes you cannot afford to get wrong, is much harder, and that is what Ampersand is building.