73% of enterprises are deploying AI without a governance or readiness framework. We help mid-market organizations adopt AI confidently — with strategy, security, and compliance built in. Plus post-quantum cryptography readiness for the threats ahead.
Harvest Now, Decrypt Later (HNDL) attacks mean adversaries are already collecting your encrypted data today, waiting for quantum computers to break it tomorrow.
NIST finalizes PQC standards
Early adopters begin migration
NSA requires PQC for national security systems
47-day certificate mandate takes effect
Cryptographically relevant quantum computers expected
of organizations lack a PQC migration roadmap
annual growth in PQC market demand
projected PQC market by 2035
typical enterprise crypto migration timeline
15 questions. Instant results. Custom report emailed to you.
Join 500+ organizations that have assessed their quantum readiness
We combine deep security expertise with hands-on engineering execution.
You get the senior expert who builds the roadmap AND implements it. No junior teams, no hand-offs to offshore resources.
CISSP-certified security strategy combined with DevOps engineering. We don't just advise — we deploy, configure, and validate.
Tool-driven cryptographic discovery, not spreadsheet audits. Our automated scanners find what manual reviews miss.
Right-sized engagements for mid-market companies. Fortune 500-grade security without the Fortune 500 overhead.
Trusted by Industry Leaders
See how we've helped leading organizations solve complex challenges.
Partnered with the National Oceanic and Atmospheric Administration (NOAA) on the "Digital Twin for Earth Observations (EO-DT) Using Artificial Intelligence" project. Developed an AI-driven binary error detection system to automatically identify and report errors in satellite images from GOES and VIIRS satellites, ensuring the data's integrity for earth observation and analysis. This work was published in the AIES journal.
Government • Satellite Operations
Rebekah Esmaili, David Daniel, Haibing Sun, Krish Narasimhan
We developed transfer learning models using ResNet-18 to automatically detect anomalies in NOAA's GOES-R ABI and VIIRS satellite instruments, replacing labor-intensive 24/7 human monitoring with real-time automated classification that runs at a fraction of the cost.
On March 24, attackers published poisoned versions of litellm to PyPI, compromising the transitive dependency tree of CrewAI, DSPy, Browser-Use, and a dozen other AI frameworks. The payload harvested credentials, deployed Kubernetes worms, and installed persistent backdoors.
Shift-left your quantum readiness by adding cryptographic policy enforcement to your build pipeline.
Manual crypto audits miss critical dependencies. Here's how automated discovery changes the game.
Harvest Now, Decrypt Later attacks are already happening. Here's why waiting for quantum computers is the wrong strategy.
Large language models are transforming enterprise workflows, but not in the ways most people expect.
How we built an AI system to automatically detect errors in GOES and VIIRS satellite imagery for NOAA's Earth Observation Digital Twin project.
Every day without a PQC migration plan is another day your encrypted data is at risk.