BN · rank #5 · 2026-09-04
ALAB
NASDAQ · $49.07B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.83 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +55.8% |
| Forward net margin Consensus forward net margin. | +31.3% |
| Net margin TTM Trailing twelve month net margin. | +30.7% |
| Margin expansion Forward minus trailing net margin (percentage points). | +0.6% |
| Forward PEG Forward P/E to growth. Below 1 is cheap for the growth. | — |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 0.15× |
| Analyst upside Spread between the consensus 12m target and the current price. | +37.9% |
| Last EPS surprise Most recent reported EPS versus consensus. | +17% |
| Market cap (USD) | $49.07B |
The AI research card
Independent qualitative review of each pick before the order is placed. On the rare day the research service is unavailable, the paper book trades on the quant ranking alone and no card appears here.
Summary
Astera Labs is a fabless semiconductor company selling CXL smart memory controllers (Leo) and AI fabric switches (Scorpio) into hyperscale cloud and AI data center customers, directly targeting memory and connectivity bottlenecks in rack-scale AI infrastructure.
Rationale
With 104% YoY revenue growth in Q2 2026, Scorpio X-Series ramping into production, Leo controllers live in Azure M-series previews, and a 0.83 composite score, ALAB is a textbook bottleneck-solver with near-term revenue visibility anchored in real hyperscaler deployments rather than sentiment alone.
Material risks
- 1Hyperscale customers—most critically Microsoft Azure—developing in-house CXL memory controllers and AI connectivity silicon would directly disintermediate ALAB's sole commercial rationale and collapse the bottleneck-solver thesis.
- 2Larger semiconductor vendors (Broadcom, Marvell) commoditizing PCIe/CXL retimers and fabric switches could erode ALAB's pricing power and compress its 76%+ gross margins as the market matures.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 2 of 3 voted to proceed.