MAGIC LENSTECHNOLOGY
Concept illustration of an FPGA platform connected to satellite, medical-imaging, autonomous and datacenter systems

AI-ACCELERATED · OUTCOME-PRICED · U.S.-BASED

Bring one hard system milestone. Pay when it passes.

Built inside your architecture, repositories and review cadence. Systems, algorithms, MATLAB/NumPy models, FPGA, DSP/SDR, firmware, emulation and validation converge under one accountable U.S. delivery boundary, with evidence, runbooks and operating knowledge transferred to your team.

OUTCOME-PRICED DELIVERYAgree on the test first. If we miss the spec, you do not pay.Explore the model →
Discuss the critical milestone ↗See the delivery method
  • 30+ organizationsSilicon, space, medical, sensing, communications and test
  • Keep product authorityYour architecture, repositories and acceptance
  • Leave the team strongerEvidence · runbooks · operating handoff
Experience across programs involving

Silicon, space, medical, sensing, communications and test systems

Serving customers since 2011 · 15 years and counting

  • Meta
  • Accenture
  • Microsoft
  • Planet Labs
  • xStellar
  • Aeva
  • Compound Eye
  • Philips Healthcare
  • Picarro
  • NextNav
  • General Radar
  • Toshiba
  • Micron
  • SanDisk
  • Western Digital
  • Rambus
  • Microchip
  • Cornelis Networks
  • Advantest
  • Teradyne
  • PDF Solutions
  • Ectron
  • Many startups
Company marks are used solely for identification. No endorsement is implied.

WHEN MAGIC LENS FITS

The risk lives between teams.

01

The algorithm works. The product path does not.

Turn reference behavior into a partitioned, measurable FPGA, firmware and host system.

02

Software is waiting for hardware.

Make emulation or FPGA prototypes repeatable and useful for real firmware and workloads.

03

The demo works. Acceptance is still vague.

Connect requirements to scenarios, tests, evidence, release configuration and accountable sign-off.

DEEP DSP LINEAGE

Signal processing for systems that must decide in real time.

Three decades at the DSP-to-hardware boundary, from Viterbi, FIR, modem, baseband and wireless test through cloud FPGA radio, RFSoC sensing, radar, resilient navigation and autonomous platforms.

Explore DSP, SDR and mission platforms →

THE EVIDENCE THREAD

Idea to product, without losing the why.

AI agents draft and transform bounded artifacts. Deterministic tools measure them. Independent critique challenges assumptions and trace gaps. Accountable engineers approve architecture and acceptance.

SPACE · FRAME INTENT

Define the mission and ground-path outcome.

Capture operating scenarios, sensor and downlink boundaries, failure consequences, environmental constraints and the evidence required for mission acceptance.

Artifact
ConOps + measurable mission acceptance
Gate
Stakeholders agree what success and failure mean
↔ Requirement traceability↔ Configuration & provenance↔ Security & IP boundaries↔ Critique & human approval
A recursive digital thread: failed evidence returns to the responsible requirement, model, partition or implementation decision.
Explore the complete method, artifact set and automation guardrails →

INDUSTRY SYSTEMS

Same rigor. Different acceptance evidence.

Select a system to see how its architecture, platform profile, failure model and product gate change the engineering plan.

Concept illustration of a satellite payload, FPGA electronics and ground link
SPACE & MISSION SYSTEMS

Sensor to ground-path evidence

Rate margin · fault recovery · telemetry integrity

 Concept illustration of a medical imaging acquisition and FPGA processing chain
MEDICAL IMAGING

Acquisition to trusted image

Numerical correlation · deterministic transport · fault state

Concept illustration of sensors, real-time compute and an autonomous robot
ROBOTICS & AUTONOMY

Timestamped perception to control

Latency budget · scenario replay · recovery

 Concept illustration of emulation racks, FPGA prototypes and target hardware
SILICON & PRE-SILICON

Model release to software readiness

Reproducibility · workload execution · debug closure

 Concept illustration of an RF and baseband system spanning FPGA, embedded control and cloud acceleration
DSP / SDR & DEFENSE SYSTEMS

Waveform intent to adaptive radio

Golden-vector correlation · spectrum awareness · bounded autonomy

Concept illustration of FPGA, PCIe, memory and network or storage paths in a datacenter server
DATACENTER & STORAGE

Descriptors to trusted completion

Queue ownership · tail latency · fault recovery

Concept illustrations, not representations of client hardware.

PRIOR PROGRAM EVIDENCE

Proof at the scale that matters.

PRODUCT SYSTEM

Vision algorithms became a licensed FPGA platform.

Reference model, RTL/HLS, PCIe/AXI/XDMA, host C, RISC-V/Linux and target demonstration were closed as one system.

Acceptance: correlated end-to-end demonstration and a surgical-robotics licensing program.
SPACE PAYLOAD

Microsatellite imaging logic sustained in orbit-facing architecture.

Camera acquisition, processor data movement, encryption, communications and board control on a Stratix 10 payload.

Acceptance: complete payload data-path behavior on target hardware.
PLATFORM PRODUCT

A multi-FPGA prototype moved from concept to acquisition.

Platform architecture, workflow, board delivery, customer evaluations and technical enablement.

Outcome: major semiconductor adoption and company acquisition.

AI-GENERATED · AUDITABLE · TESTABLE

Every artifact keeps its path to evidence.

AI can draft requirements, UML/SysML views, interfaces, implementation and tests. Persistent IDs, versioned source, deterministic checks and human release authority keep the result traceable through failure analysis and root-cause confirmation. For flight, defense and invasive medical systems, generated code is never accepted as its own audit evidence.

See the sequence, state and evidence models →
Agents propose

Specifications, transformations, tests, documentation, triage hypotheses and repeatable workflows.

Tools measure

Compilation, lint, formal, simulation, emulation, profiling, target execution and correlation.

Critics challenge

Trace gaps, unsafe assumptions, unreachable states, interface conflicts and unsupported conclusions.

Engineers accept

Architecture, risk disposition, IP boundaries, waivers, release configuration and product gates.

SHARED DELIVERY RISK

Outcome-based pricing: if we miss the spec, you do not pay.

AI makes code faster. It does not own timing closure, hardware bring-up, failure isolation or acceptance. Choose one hard milestone and its written test. Magic Lens owns delivery; your team gets a finished result it can defend internally without betting its budget.

Each milestone uses a written test, named dependencies, a clear acceptance owner and change control. It never promises certification, silicon success or commercial results outside our control. Compare all engagement models and safeguards →

START WITH THE BOTTLENECK

What milestone cannot be allowed to slip?

Share the program boundary, current evidence and timing pressure. Do not include confidential design information.

info@magiclenstech.com

We usually reply within one business day. If you would rather send plain email, info@magiclenstech.com reaches the same place.