QSL is a technology company specializing in AI, quantum computing, and wireless solutions for enterprise customers. We deliver end-to-end solutions from software optimization to hardware acceleration.

We work with Fortune 500 companies and fast-growth tech leaders in finance, telecom, defense, aerospace, and energy sectors. Our customers are typically CIOs, CTOs, and product leaders seeking competitive advantage through advanced technology.

We own the entire stack from algorithm to hardware. No vendor lock-in. We have deep PhDs in quantum, signal processing, and ML with production deployment experience. We focus on measurable ROI, not hype.

Typical customers see 30-60% reductions in compute costs through quantization, compression, and FPGA acceleration. Timeline to ROI is typically 90 days.

Modern quantization techniques (GPTQ, QAT, KD-QAT) preserve accuracy while dramatically reducing memory and compute. Most models maintain >99% accuracy after quantization.

Estimates range from 10-15 years, but "harvest now, decrypt later" threats exist today. Adversaries are already capturing encrypted traffic for future decryption. Start quantum-safe migration now.

No. Hybrid quantum-classical algorithms deliver value on current NISQ hardware (IBM, Google, IonQ). We also provide simulated quantum solutions for prototyping and algorithm development.

Post-quantum cryptography uses mathematically hard problems (lattices, multivariate polynomials) that resist both classical and quantum attacks. NIST has standardized several PQC algorithms. We help you implement them.

AI optimizes signal processing (neural receivers), compensates for nonlinearities (DPD), manages interference, and predicts channel conditions in real-time. Typical gains: +20-30% throughput, -15-20% power consumption.

Yes. Many of our solutions are software-only and deployable on existing DSPs and FPGAs. Hardware acceleration is optional and accelerates ROI.

DPD is a technique that preemptively corrects nonlinearities introduced by power amplifiers. ML-based DPD learns the PA characteristics and adapts in real-time for optimal linearity and efficiency.