Industries
Technology
In technology, AI is the product, not a tool bolted onto it. Data moving through the model cannot leave the provider's network or be co-mingled across tenants. We deliver AI you can defend on SOC 2, customer data separation, and data residency - inside a stack the platform owns and operates, backed by evidence that survives an audit.
What runs through Technology - and what cannot leave
The substance behind that posture, in scannable form. Each card names a piece of tenant separation and data residency reality our delivery addresses, rather than a generic compliance label.
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AI is the product, not a bolt-on
AI-native products and platforms, model operations at customer scale, code and engineering productivity lifted with AI assistance, and multi-tenant AI services where each tenant's data, prompts, and completions stay separated.
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Tenant separation and data residency
Customer tenant data, prompt and completion logs, fine-tuning corpora, training estates, and proprietary source code and IP are strictly separated to prevent co-mingling.
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Regimes the posture holds against
EU GDPR for customer tenant data, and the EU AI Act for deploying AI models to customers; US SOC 2 (and SOX where applicable); LATAM GDPR-influenced regimes plus LGPD-readiness.
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What a shared-cloud deployment cannot defend
A generic shared-cloud deployment crosses the tenant boundary promised in the contract. A single co-mingled weight or residency breach at a jurisdictional edge terminates the relationship.
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Where pilots collapse
Pilots fail when customer tenant data lands in a shared cloud tenant. They also fail when a roadmap sequences a model before the private infrastructure it requires, or when a build is never validated against the platform's own tenant data.
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How the delivery retires those failures
Strategy with teeth is the only honest offer. Diagnosis scopes the tenant-defensible scope. Sequencing secures your network before deploying models. Validation exercises tenant isolation against real multi-tenant workloads before capital commits.
Processes we automate
The first wave of technology processes we automate, named process by process: agents read the repositories, signals, and records your teams already hold, extract and flag with sources cited, and hand a draft or an alert to a named engineer who reviews and decides.
Development
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Code review and PR scanning
Every pull request is scanned against your standards before review, with advisory comments that flag style, performance, and tech debt for the reviewing engineer.
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Repo-grounded code assistance
Code answers grounded in your own repositories and standards, with the source files cited, so engineers verify every suggestion against the real code.
Security
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SAST/DAST scanning with agent triage
Static and dynamic vulnerability scans run continuously, and agents triage the findings, deduplicating and ranking them so engineers act on signal instead of noise.
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Security-questionnaire drafting from your own controls corpus
Agents draft answers to customer security questionnaires from your own controls corpus, with the evidence linked, ready for the security team to review before anything is sent.
Product
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Feedback into structured user stories
Agents read raw feedback from every channel, cluster the recurring themes, and hand product owners structured user-story drafts to accept, edit, or reject.
IT service management
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Ticket triage and routing
Every inbound ticket is classified, prioritized, and routed to the right queue, with the context a specialist needs drafted alongside it.
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Knowledge-base auto-answers for recurring support themes
For questions your support team answers again and again, agents draft answers grounded in your internal knowledge base, and a human publishes them under policy.
Site reliability engineering
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FinOps right-sizing across cloud and on-premise
Agents scan resource usage across your cloud estates and your own hardware, draft right-sizing recommendations, and leave every change decision with your engineers.
Capabilities operated
Technology platforms build on the same methodology and capabilities. Customer tenant data, model assets and training data, and confidential source and IP stay inside your network, so customer-data separation, residency, and SOC 2 controls hold from diagnosis through to measurable ROI.
- Agentic processes See how intake routing and runbook automation run as agents inside your network.
- Custom AI development See how we design and build AI agents that guarantee tenant isolation.
- On-premises AI infrastructure See how we size the infrastructure footprint that maintains tenant separation.
Where the proof lives
The framing above is a posture. The validated engineering that holds customer-data separation and residency intact is what Building and Validation delivers before major capital commits. We size your private stack, build the model on your real tenant and code base, and validate against real multi-tenant workloads. You procure only what validation proves necessary.