Transformation
Cybersecurity
Security architecture, AI-era threat defense, and compliance engineering for regulated industries — security that enables the business instead of vetoing it.
Overview
Why it matters
The threat economics keep worsening: IBM puts the average cost of a data breach in the multi-million-dollar range, ransomware has become a professionalized industry with affiliate programs, and attackers now use AI to scale phishing and vulnerability discovery. Meanwhile your own attack surface grows with every cloud account, SaaS contract, API, and — newly — every LLM integration and AI agent with tool access. Security teams are asked to defend more with the same headcount, and the gap is where incidents live.
Our practice closes that gap with engineering, not fear. We design security architectures on zero-trust principles — identity as the perimeter, least privilege enforced in code, segmentation that contains what prevention misses. We embed security into delivery pipelines so vulnerabilities are caught at commit time, not audit time. And we operate detection and response capabilities that assume compromise and measure themselves on time-to-detect and time-to-contain, not on the thickness of the policy binder.
Two things distinguish the practice. First, AI security on both sides: we secure AI systems (prompt injection defense, agent permission models, model supply-chain integrity — the OWASP LLM Top 10 made operational) and we use AI in defense (triage augmentation, anomaly detection at scales analysts can't match). Second, compliance as engineering: SOC 2, ISO 27001, HIPAA, PCI DSS, and DORA obligations mapped to automated controls with continuously collected evidence — so audit season becomes a report, not a fire drill.
Business challenges
The problems this practice exists to solve
An attack surface growing faster than the team
Multi-cloud estates, hundreds of SaaS apps, APIs, remote endpoints — and now AI integrations — each a potential entry point, mapped by attackers more systematically than by their owners.
Compliance as a permanent fire drill
SOC 2, ISO 27001, HIPAA, PCI DSS, DORA — overlapping frameworks evidenced manually, quarter after quarter, consuming the security team's capacity without making anything more secure.
Detection measured in months
Industry mean time to identify a breach still runs in months. Logs exist but nobody correlates them; alerts fire but drown in noise; the SOC learns about incidents from customers or journalists.
AI systems shipped without a security model
LLM apps vulnerable to prompt injection and data exfiltration, agents with over-broad tool permissions, and shadow AI usage across the workforce — a new attack class most security programs haven't caught up with.
Our solution
How we engineer it
We start from architecture, because controls without architecture are patches. A zero-trust design makes identity the control plane: strong authentication everywhere, least-privilege access enforced through policy-as-code, network segmentation that turns a breach into a contained event, and encryption with managed keys as the default state of data. In cloud estates this is implemented in the same Terraform that builds the infrastructure — guardrails that new workloads inherit rather than policies they're asked to read.
Security shifts into the delivery pipeline: SAST, dependency and container scanning, secrets detection, and infrastructure policy checks run on every commit, with findings routed to the engineer who can fix them in minutes. Threat modeling happens at design time for the systems that matter, and penetration testing validates the result — including AI-specific assessments: prompt injection and jailbreak resistance, agent permission audits, retrieval access-control verification, and model supply-chain review against the OWASP LLM Top 10.
Then we operate for the attacks that get through anyway: detection engineering on a modern SIEM (Sentinel, Splunk, or Elastic) tuned to your actual environment rather than vendor defaults, AI-assisted triage that cuts alert noise before it burns out analysts, rehearsed incident-response runbooks with defined roles, and tabletop exercises with your leadership — because the worst time to design your ransomware response is during one. Compliance rides on top as automation: controls mapped once across your frameworks, evidence collected continuously from the systems themselves, and audit readiness as a dashboard rather than a quarter.
Capabilities
What cybersecurity covers
Security architecture & zero trust
Identity-centric architectures with least-privilege enforcement, segmentation, and encryption by default — implemented as code in your cloud and network estate.
Cloud & infrastructure security
CSPM, landing-zone guardrails, workload identity, and Kubernetes hardening across AWS, Azure, and GCP — findings fixed in Terraform, not in tickets.
Application & pipeline security
Threat modeling, SAST/DAST and dependency scanning in CI/CD, secrets management, SBOMs, and penetration testing — security at commit time, not audit time.
AI & LLM security
Prompt-injection defense, agent permission models, retrieval access-control audits, AI usage governance, and red-teaming against the OWASP LLM Top 10.
Threat detection & response
Detection engineering on Sentinel/Splunk/Elastic, AI-assisted triage, incident-response runbooks, and tabletop exercises — measured on detect and contain times.
Compliance engineering
SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR, and DORA mapped to automated controls with continuous evidence collection — audit readiness as a standing state.
Technology stack
Tools we deploy to production every week
Pragmatic about tools, opinionated about architecture — the platforms below are the ones this practice ships with, chosen per engagement on evidence.
Identity & Access
- Entra ID
- Okta
- CyberArk
- HashiCorp Vault
- SailPoint
Detection & Response
- Microsoft Sentinel
- Splunk
- Elastic Security
- CrowdStrike
- Defender XDR
Cloud & Pipeline Security
- Wiz
- Prisma Cloud
- Snyk
- Semgrep
- Trivy
- Open Policy Agent
GRC & Evidence
- Vanta
- Drata
- ServiceNow GRC
- Custom evidence pipelines
Implementation process
Five stages. No surprises.
A delivery model refined over 250+ engagements — sequenced so leadership gets visibility and your teams get momentum.
Assess & prioritize
Threat-informed assessment of your estate — architecture, identity, cloud posture, application pipeline, AI usage — producing a risk-ranked roadmap, not a 400-finding PDF.
Architect the target state
Zero-trust reference architecture, control framework mapped across your compliance obligations, and guardrail designs reviewed with engineering — security that ships as code.
Implement guardrails
Identity hardening, cloud guardrails in Terraform, pipeline security integration, and AI security controls — sequenced by risk reduction per unit of engineering effort.
Build detection & response
SIEM detection engineering tuned to your environment, response runbooks, on-call design, and tabletop exercises with leadership — rehearsed before it's real.
Operate & evidence
Continuous posture monitoring, quarterly purple-team validation, compliance evidence automation, and metrics reporting — detect time, contain time, control coverage.
Use cases
Where enterprises apply it
Zero-trust transformation
Migrating from perimeter-and-VPN architecture to identity-centric access across cloud and on-prem — without a big-bang cutover that breaks the business.
Cloud security posture remediation
Systematic hardening of multi-cloud estates: guardrails in code, workload identity, and posture findings burned down at the Terraform layer.
SOC 2 / ISO 27001 readiness
Control implementation and evidence automation that takes a scaling company from zero to audit-ready — and keeps it there without heroics.
AI deployment security review
Pre-production assessment of LLM apps and agents: prompt-injection testing, permission audits, data-flow review, and a remediation plan security can sign.
Detection & response uplift
SIEM detection engineering, alert-noise reduction, and incident runbooks that cut mean detect-and-contain times from months to hours.
Ransomware resilience program
Segmentation, immutable backups, privileged-access hardening, and rehearsed recovery — tested with tabletop and restore exercises, not assumed.
Outcomes
Results clients report to their boards
11 min
median time-to-detect on high-severity events after detection engineering, from hours
87%
reduction in critical cloud posture findings within two quarters, fixed as code
6 wks
to SOC 2 Type I readiness for a scaling platform company, with evidence automated
0
successful prompt-injection exfiltrations in post-hardening red-team exercises across our AI deployments
FAQs
Questions leaders ask us
Direct answers on cybersecurity — the same ones we give in the first consultation.
Related services
Practices that pair with this one
Ready to put cybersecurity to work?
In a 45-minute consultation, our architects map your highest-ROI opportunity, outline a delivery plan, and give you a realistic budget range — no obligation.