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CNC — Concurrent Technologies News Story

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UK's Concurrent Technologies H1 orders more than double on contract win

UK's Concurrent Technologies H1 orders more than double on contract win


Overview

  • UK embedded computing firm's H1 revenue and pretax profit hit record levels

  • Order intake for H1 more than doubled yr/yr, driven by a large European contract

  • Company enters H2 with strong backlog and momentum after post-period contract win


Outlook

  • Concurrent Technologies expects full-year 2026 results in line with market expectations

  • Company sees strong demand, healthy backlog and pipeline conversion supporting H2 FY26

  • Consensus market expectations for FY26 are revenues of £53m and profit before tax of £8m


Result Drivers

  • ORDER MOMENTUM - H1 order intake rose 110% yr/yr, driven by demand across key geographies and end markets, including a large European contract

  • DESIGN WIN CONVERSION - Increased conversion of earlier design wins into production orders supported revenue in the period

  • SYSTEMS BUSINESS CONTRIBUTION - The Systems business secured about $8 mln of orders and delivered a profitable first half


Company press release: ID:nRSM9762La


Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

H1 Revenue

GBP 23.10 mln

H1 Orders

GBP 46.90 mln

H1 Pretax Profit

GBP 3.30 mln


Analyst Coverage

  • The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 5 "strong buy" or "buy", no "hold" and no "sell" or "strong sell"

  • The average consensus recommendation for the semiconductors peer group is "buy"

  • Wall Street's median 12-month price target for Concurrent Technologies PLC is GBp275.00, about 10% above its July 10 closing price of GBp250.00

  • The stock recently traded at 31 times the next 12-month earnings vs. a P/E of 24 three months ago


For questions concerning the data in this report, contact Estimates.Support@lseg.com. For any other questions or feedback, contact reuters.support@thomsonreuters.com.


(This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)

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