DataAgent emerged from stealth with the launch of its AI-native infrastructure remediation platform and $10 million in pre-seed funding led by MizMaa Ventures and Alicorn Venture Partners. The company plans to use the financing to bring its remediation-first platform to market and accelerate customer adoption across North America.
DataAgent was founded in January 2026 by Ishay Yaari, CEO, and Nati Shalom, CTO, who previously worked together at cloud orchestration company Cloudify, which was acquired by Dell in 2023.
The company currently has 15 employees and is recruiting additional go-to-market personnel in the United States and Israel.
DataAgent is developing what it calls a Digital Immune System for modern applications. The platform functions as an AI-native autonomous site reliability engineer for Kubernetes and connected cloud infrastructure.
Rather than functioning primarily as an observability platform that identifies an infrastructure problem and alerts an engineer, DataAgent is designed to automatically remediate production issues when they occur.
The platform operates within customers’ cloud-native control planes and integrates with existing observability tools as an overlay, allowing companies to deploy DataAgent without replacing their existing monitoring infrastructure.
Its agents collect signals directly where infrastructure and telemetry reside, identify production faults and take user-defined, guardrail-controlled actions to restore service.
DataAgent said the architecture can also reduce the amount of telemetry that needs to be transferred to external observability vendors. Only information required for deeper investigation is forwarded outside the environment when necessary.
The company argues that this approach could lower observability costs while reducing the time required to resolve production incidents.
DataAgent’s platform combines a production remediation engine with a pre-production system designed to prevent certain failures before software is deployed.
The company said the two systems work together as a continuous prevention and remediation loop, allowing the platform to learn from both incidents it resolves and problems it prevents.
DataAgent’s approach reverses the traditional observability workflow.
Conventional systems generally detect an issue, gather and analyze telemetry, identify a root cause and then involve an engineer who makes a change. DataAgent instead reads system state, topology and configuration information within the customer’s own environment and prioritizes restoring service with a verified action.
A more extensive root-cause analysis can then be performed after the service has recovered.
The company said this remediation-first architecture is designed to reduce mean time to resolution while also limiting the amount of data that customers need to send to outside monitoring platforms.
DataAgent cited Grafana Labs’ 2025 Observability Survey, which found that observability spending averages approximately 17% of total compute infrastructure spending.
The platform includes four primary elements.
Its remediation-first architecture can autonomously resolve approved classes of incidents using controls established by the customer.
DataAgent also builds what it describes as a 360-degree understanding of an organization’s infrastructure, incorporating topology, code, environment and configuration information rather than relying only on individual logs and traces.
During deployment, the platform goes through a discovery process to determine which types of failures it can safely remediate. It can then adapt to additional failure modes over time, while incidents that have not reached the required level of confidence can continue to be routed to human operators.
DataAgent is also making its infrastructure agent open source. The agent can be deployed independently at no cost, while the company offers a paid SaaS tier for fleet management and orchestration.
The company is positioning the open-source model as a way to address concerns enterprises may have about placing closed proprietary software inside sensitive production environments.
DataAgent also expects its local processing architecture to provide financial benefits.
Instead of continuously ingesting and indexing large quantities of logs, its root-cause analysis technology focuses deeper inspection on the portions of applications and infrastructure most relevant to system stability.
The company claims customers could reduce observability spending by as much as 90%, depending on their environment and existing infrastructure.
KEY QUOTES:
“In DataAgent, observability is just one feature – the real product is a self-healing infrastructure. We pair a production remediation engine that fixes failures after they happen with a pre-production engine that blocks them before code ever ships. And they are not separate products: prevention and remediation are fused into one continuous lifecycle, so the system gets smarter with every failure it stops and every incident it resolves.”
Ishay Yaari, Co-Founder and CEO of DataAgent
“Applying rapidly evolving AI technology to major pain points with transformational results is the holy grail. DataAgent is doing exactly that by moving observability beyond insight and toward action.”
Catherine Leun, Co-Founder and Partner at MizMaa Ventures
“DataAgent is attacking one of the most expensive and persistent problems in modern software infrastructure: systems that can tell engineers something is broken, but cannot safely fix it. What attracted us to DataAgent is the company’s ability to combine autonomous remediation with a deployment model that keeps customer infrastructure and telemetry under the customer’s control.”
Alexander Assim, Managing Partner of Alicorn Venture Partners
“The industry has spent 15 years building better ways to watch production and charging more for it every year. Legacy tools have become data-heavy and reactive, while recent attempts to bolt AI copilots onto this broken model have not changed the outcome. We have built DataAgent the other way around. Our platform and agents act where the data already sits, restore health first and earn autonomy one fault class at a time. Autonomy is not an add-on feature for observability; it is a fundamental architectural shift that slashes costs as a direct result.”
Nati Shalom, Co-Founder and CTO of DataAgent
“In ten years, no one has ever heard an engineering leader say their organization’s observability costs went down and that is no accident. When a vendor’s revenue is your data ingest, it cannot cut your bill without cutting its own. DataAgent can run alongside your existing tools, while filtering out the noise and rerouting data only when an incident demands it. There is no need for an expensive second copy of your data and everything pulled live from the source so customers can cut up to 90% of their observability spend.”
Ishay Yaari, Co-Founder and CEO of DataAgent
