Innovation that Never Stops.

Security, Governance & Value Assurance

TMT clients are usually further along with AI than any other sector we serve, so the question is rarely ‘should we’ and almost always ‘can we prove this is safe to ship.’ We run AI security assessments, data foundation assessments and agentic AI opportunity assessments against production estates, model risk into the data pipeline rather than just the model, and stand up governance that maps to recognized AI frameworks without stalling release velocity.

For companies embedding AI in customer-facing products, we run adversarial AI testing and purple teaming so controls are validated rather than assumed, and manage the AI attack surface continuously as it changes. Where AI is being scaled internally, our value transformation and ROI acceleration work keeps the spend tied to outcomes leadership can defend.

This is the core of most TMT engagements: the cloud estates, data centers, networks and platform layers the business actually runs on.

We deliver secure-by-design architecture across multi-cloud and hybrid environments, infrastructure-as-code and container security, segmentation across IT, network and broadcast or OT systems, and secure log-pipe-lake design so telemetry is usable rather than merely retained.

Risk-based vulnerability management and attack surface management are sized for environments that deploy continuously; the goal is remediation that fits inside the release train, not a quarterly scan report.

For data center and OT-adjacent estates we align to IEC 62443, NIST and ISO standards without pretending a carrier network is a factory floor.

TMT clients manage a compliance surface that spans jurisdictions, product lines and acquired entities all at once. We build the strategy and roadmap, the policy framework (including governance for secure and ethical AI adoption), and the metrics that leadership and the board will actually use.

Third-party risk carries disproportionate weight in this sector given the depth of SaaS and open-source dependency, so we build programs that scale to thousands of vendors rather than a spreadsheet of the top fifty.

On the transaction side we support the full M&A lifecycle, from pre-deal diligence (including AI-specific diligence and adversarial testing) through post-close integration of network, identity and cloud environments.

Identity & Access Management in TMT has two faces: a workforce and contractor population that turns over constantly, and a consumer or subscriber base measured in the millions.

We modernize identity governance across workforce, contractor, third-party and non-human identities, deploy privileged access across cloud, DevOps and AI systems without slowing engineering down, and design CIAM with SSO, MFA and passwordless authentication where user experience is a commercial issue rather than only a security one.

The fastest-growing piece is non-human identity: service accounts, machine identities and now AI agents acting on their own credentials. Most TMT estates have not yet brought any of it under governance, and we treat it as a first-class identity population rather than an exception list.

Detection, Response & Threat Management

TMT environments generate enormous telemetry volumes and attract well-resourced adversaries: nation-state actors after intellectual property and network access, and criminal groups after subscriber data and content.

Our Cyber Fusion Center runs managed SIEM, EDR and SOAR on a follow-the-sun 24x7x365 model, vendor-agnostic, adapting to the stack the client has already built rather than demanding a rip-and-replace.

Detection engineering is written to the client’s own environment, including cloud-native and AI workloads that generic content packs miss entirely.

Threat hunting, adversary simulation and intelligence from our research labs feed back into the architecture work, so findings become design changes rather than tickets.