Hatz AI raises $24 million to expand its enterprise artificial intelligence platform for MSPs

Kindo, a company specializing in enterprise artificial intelligence management, has successfully secured a funding round of $30 million. Leading investors in this round included Crosspoint Capital and Forgepoint Capital, with participation from TFX Capital and Circle Rock Capital. Existing investors involved in the deal included Drive Capital, Riot Ventures, RRE Ventures, and Eniac Ventures.

The new round increases Kindo's total funding to $57.6 million. The company, founded in 2022 and based in Venice, California, has not yet disclosed the official name of this round. In 2026, the company demonstrated approximately 800% year-over-year revenue growth.

The capital raised will be used to scale its go-to-market operations, develop an Enterprise AI Control Center, and enhance Deep Hat models and add-ons.

Kindo provides centralized management for searching, administering, and monitoring enterprise AI agents. The company's software detects so-called 'shadow AI' within organizational environments by aggregating agent activity, permissions, costs, and performance into a unified view. This solution addresses a significant challenge faced by enterprise IT teams.

Companies use autonomous agents to perform a wide range of tasks, from security control to supply chain management. However, IT, security, finance, and compliance departments are often unaware of these autonomous agents' usage. Kindo gateways track and validate agent calls to connected data sources, while also monitoring interactions with software and sanctioned AI models.

Kindo's identification system utilizes corporate access rights for employees and agents, which can be supplemented by administrators. Furthermore, Kindo offers a dedicated 'agent container' for critical use cases. Previously, the main drivers for the need for AI agent management were security and compliance. Now, the issue is the operational cost of autonomous intelligent systems.

Kindo's AI Control Center provides financial departments with transparency regarding expenditures. The Deep Hat Sift tool helps eliminate extraneous information from security queues by tracking token usage and logging the successes and failures of each agent, including failed tasks in reports. Organizations can view spending by employee, agent, department, and project, and set budgets, alerts, and budget limits.

The platform allows for the identification of unproductive agents and excessive model usage. Financial teams can analyze each agent's activity and compare its results against input data. Additional cost optimization tools are available through Kindo's Deep Hat products.

Kindo is utilized in manufacturing processes by various enterprises across different industries. Clients include companies from the financial services and professional services sectors, as well as healthcare and aviation. The company has received SOC 2 Type II certification.

One example of successful implementation is Aireon, a global data provider for aviation. Aireon uses Kindo for threat hunting and for first and second-level security operations. According to Aireon's CISO, the platform saves the company over $2 million annually, which was noted in May 2026.

Kindo's steps come amid the broader adoption of autonomous agents in business. Nevertheless, enterprises continue to address issues of visibility and accountability. Access, performance, and costs will remain key aspects as adoption scales, and Kindo now has additional resources to meet these needs.

Larridin, a company based in South San Francisco, has raised $30 million to develop its corporate artificial intelligence measurement platform. The company helps businesses understand the financial impact of implementing artificial intelligence. With this funding round, Larridin's total funds raised have reached $47 million.

Pelion Ventures led the Series A investment round. Other existing investors participating in the deal include Andreessen Horowitz and Gradient Ventures. New investors in the round include GFT, W23, Thayer, DG Daiwa Ventures, Alumni Ventures, and Cougar Capital. The company has tracked over two billion AI-related sessions.

The funds will be used to develop the product and expand the team. The startup's platform connects data on AI implementation, performance, and financial information from various organizations. This allows business leaders to identify opportunities and make more informed investment decisions.

Larridin is targeting a growing problem among enterprises that are adopting artificial intelligence. Most companies track AI activity but do not understand what results this activity generates. The company's platform correlates employee and agent activity with operational outcomes.

It enables businesses to assess where tools provide a return on investment and where costs should be cut. Larridin reported that the average increase in measurable team output was 47%. Furthermore, the company notes a median AI cost optimization of $2.4 million within the first year of client operation.

Larridin's client base includes SurveyMonkey, Vertiv, Klaviyo, Gainsight, and Globality. Other clients are TigerConnect, EcoVadis, and Sundt. The platform also identifies differences in AI spending across various teams. In one client project, one engineer accounted for approximately 65% of the team's total AI costs in one week.

Another analysis showed a sixty-sixfold difference in the cost of a single submitted engineering change. Two AI tools performed similar work but generated significantly different costs. This data demonstrates why mere adoption metrics are insufficient for a complete picture.

Along with the funding announcement, Larridin presented its quarterly report on the impact of AI on engineering. The Q3 2026 report covers the level of AI adoption among over a thousand software engineers. The report identifies workflow violations in software development.

The proportion of code merge requests executed by AI increased from 35% in April to 62% in September. However, the higher workload also created additional pressure on the review process. The median waiting time for initial human code review increased by 50% over the same period.

These results point to increasing pressure points for engineering teams. An increase in AI-generated work does not guarantee faster software delivery. Organizations must consider both review throughput and code quality.

Larridin will scale its staff in parallel with product development. Jeff Kierl, General Partner at Pelion Ventures, stated that 'Larridin provides transparency on how dollars spent on corporate AI translate into quantifiable business results.'

Larridin enters a market where corporate AI spending continues to draw close scrutiny. Businesses are moving from initial adoption to stricter financial control. The company was founded in 2024 and has expanded its client base. Larridin's goal is to provide measurement for both employees and software agents.

The platform supports organizations across various industries and business functions. Alex Rampell, General Partner at Andreessen Horowitz, also highlighted the company's potential, calling its technology an important standard for measuring corporate AI. The investment will support additional capabilities as enterprises demand greater transparency. The broader trend goes beyond measuring software subscriptions; companies are increasingly seeking to understand the link between AI spending and completed work. This latest funding will support efforts to improve accountability for AI investments.

San Francisco-based startup Collective has raised $100 million to develop its financial services designed for individual entrepreneurs. The platform integrates various business functions, including accounting, payroll, tax reporting, and other services.

The funding includes a $40 million Series B round, as well as $60 million from General Catalyst's Customer Value Fund. General Catalyst, QED Investors, and Gradient Ventures led the equity round; Intuit Ventures, FT Partners, and SemperVirens also participated.

Collective's founder is Hooman Radfar, who learned about the financial benefits of business tax planning through his family. Reports indicate that his father's business structure helped him save significantly more on self-employment taxes than his mother's.

The $60 million comes from General Catalyst's Customer Value Fund. Unlike traditional equity financing, this arrangement supports client acquisition through a revenue-based repayment model. Thus, the total funding package reached $100 million.

The company has not disclosed its current valuation or the specific repayment terms for the customer acquisition mechanism. General Catalyst has used similar mechanisms to support other companies in the financial and business software sectors, but the specific terms of the Collective agreement have not been made public.

A separate $40 million Series B round provides traditional equity financing for broader company expansion. Collectively, these funds support both product development and customer base growth. General Catalyst partner Pranav Singhvi noted that small businesses represent a significant opportunity and expects AI adoption to accelerate growth in this market.

Previously, Collective raised $8.65 million in a seed round in 2020, followed by $20 million in a Series A round in 2021, and $50 million in July 2023. The market potential is assessed as substantial.

Collective serves individual entrepreneurs, independent consultants, and freelancers. The company's comprehensive membership provides business registration, bookkeeping, invoicing, payroll, and tax filing. Collective members are also offered health and business insurance.

In July 2026, the company launched its Insurance Center in partnership with Coverdash and Solo Health. In April 2026, Collective acquired the AI bookkeeping startup Open Ledger. The new funding will help expand these offerings into the banking sector and add additional insurance products.

Collective reports 127% year-over-year business growth and cumulative tax savings of $350 million for its members. According to the company, its most profitable clients save up to $40,000 annually. However, the company has not disclosed revenue or customer numbers, so these figures remain metrics provided by the company itself. The company estimates that over 30 million businesses in the United States have no employees, and AI tools can help a larger number of independent founders manage complex financial operations without hiring specialized teams.

Collective faces competition from financial platforms serving independent workers and small businesses, notably Lettuce Financial. The market has also experienced turbulence, including the sudden closure of Bench in December 2024. Other AI bookkeeping startups target audit firms and corporate finance teams, which differs from Collective's approach focused on the needs of individual entrepreneurs. Collective's strategy is to automate more workflows within a single integrated platform, potentially reducing the need for separate tools for accounting, taxation, and insurance. Radfar believes that AI can enhance the efficiency of independent founders, and the next phase of the company will focus on testing its integrated financial platform's ability to deliver on this promise at scale.