RADCOM cuts FY26 revenue guidance to $57-63M on delays

2 min read     Updated on 30 Jul 2026, 09:12 PM
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AI Summary

RADCOM Ltd. reduced its FY26 revenue guidance to $57-63M, citing customer deployment delays driven by higher component costs and supply constraints. Preliminary Q2 revenue is approximately $12M, with no cancellations reported. Management expects non-GAAP profitability for FY26 and double-digit growth in 2027.

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RADCOM Ltd. (NASDAQ: RDCM) lowered its full-year 2026 revenue guidance to a range of $57 million to $63 million, citing customer deployment delays driven by higher component costs and supply constraints. The network assurance solutions provider announced preliminary second quarter revenue of approximately $12 million on July 30, 2026, ahead of its formal earnings release scheduled for August 12, 2026. This downward revision signals a contraction in annual financial expectations, with the new midpoint of $60 million reflecting timing headwinds rather than a decline in underlying demand.

The reduction in the outlook stems from delayed customer purchasing decisions that became evident in the final weeks of the second quarter. RADCOM’s Chief Executive Officer, Benny Eppstein, stated that these delays are impacting several customers and could continue to affect revenue timing through the balance of 2026. Importantly, management clarified that the company did not experience any order cancellations or competitive losses, characterizing the slowdown as a temporary shift in deployment schedules.

Financial Outlook Adjustment

Management based the revised guidance on preliminary analysis of second-quarter performance. The expectation of approximately $12 million in revenue for the quarter forms the basis for the adjusted annual projection. By narrowing the range to $57 million–$63 million, RADCOM is providing investors with a more constrained view of its potential annual earnings.

Metric Value
Q2 Preliminary Revenue ~$12 million
FY26 Revenue Guidance Low $57 million
FY26 Revenue Guidance High $63 million
FY26 Midpoint $60 million

Despite the revenue headwinds, management expects RADCOM to remain profitable on a non-GAAP basis for full-year 2026. The company anticipates returning to double-digit growth in 2027 as customer deployment activity normalizes.

What the Numbers Show

The decision to cut guidance suggests that recent operational results have fallen short of earlier internal targets or market expectations. While the company did not specify the exact magnitude of the cut relative to prior guidance, the establishment of a $60 million midpoint implies a significant recalibration of its growth assumptions for 2026. Investors will look to the upcoming August 12 earnings call for further details on the drivers behind this revision, including any changes in customer demand or competitive dynamics affecting the network assurance sector. The distinction between timing delays and actual demand erosion is critical for assessing the sustainability of the company’s long-term growth trajectory.

How might the ongoing supply constraints and higher component costs impact RADCOM's gross margins in Q3 and Q4 2026?

What specific cost-cutting measures or operational adjustments is management implementing to maintain non-GAAP profitability despite the revenue shortfall?

Which specific customer segments or geographic regions are most affected by the deployment delays, and is there a risk of these delays becoming permanent cancellations?

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Radcom launches analytics module for real-time network data

1 min read     Updated on 22 Jun 2026, 06:00 PM
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Reviewed by
Riya DScanX News Team
AI Summary

Radcom has launched the RADCOM ADM module, allowing network data analysts to define and deploy datasets, KPIs, and alarms in real time without vendor support. Powered by the RADCOM RASE engine, it offers 10-second resolution and integrates with RADCOM ACE and Neura's AI layer. The module will be available in Q3 2026.

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Radcom has launched the RADCOM ADM module to enable network data analysts to define, configure, and deploy datasets, KPIs, and alarms in real time without requiring vendor engagement. The module addresses constraints in traditional analytics, which often lack dynamism, cost-efficiency, and real-time capabilities. By allowing operators to adapt data structures on the fly, RADCOM ADM aims to enhance agility for network operations, planning, and business intelligence teams.

The module is powered by RADCOM RASE (Real-time Adaptive Streaming Engine), a new analytics engine that combines dynamic aggregation with resolution as fine as 10 seconds. This technology surfaces insights into subscriber experience as events unfold. The development required a fundamental rebuild of Radcom's core infrastructure, including new in-memory databases, processing architecture, and scaling approaches to support Tier-1 operator scale.

RADCOM ADM integrates with Radcom's existing ecosystem, drawing on RADCOM ACE assurance data and external feeds. It establishes a shared analytics foundation where every KPI defined in ADM flows into RADCOM ACE network analytics, RADCOM AIM anomaly detection, and RADCOM Neura's agentic AI layer. This creates a single source of truth across the platform using the same KPI identifier.

"The pace at which network conditions change demands analytics that can keep up," said Eran Dotan Rosenberg, Vice President of Product Management at Radcom. "With RADCOM ADM, operators can define the data they need, at the resolution they need it, and the moment they need it. The platform adapts to the operator, not the other way around."

The module provides an Integrated Development Environment (IDE)-like workspace for network data analysts. Teams such as network operations, planners, and business functions like marketing and fraud management can access deployed data directly with appropriate permissions. Streaming data flows into RADCOM Neura's agentic AI layer, serving as the data foundation for reliable and accurate automated actions.

RADCOM ADM will be generally available to RADCOM ACE customers in the third quarter of 2026 as a licensed module of the RADCOM ACE platform.

How will the transition to the new in-memory database architecture impact the total cost of ownership for Tier-1 operators?

What competitive advantages does the 10-second resolution offer compared to emerging real-time analytics solutions from rivals?

Will the agentic AI layer require a period of learning before automated actions become reliable for critical network operations?

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