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SaaS & Technology

AI Evaluation & Red Teaming for SaaS & Technology

AI Evaluation & Red Teaming for saas & technology, built around the constraint that defines the sector: per-tenant economics and enterprise security review decide whether a feature can ship.

Regulations in scope
4
Systems we integrate
4
Typical first release
6 weeks
Start a conversationSee pricing

What changes when it is saas & technology

Orqent Labs red-teams AI systems before launch and leaves behind the evaluation harness your team runs on every change.

In saas & technology, per-tenant economics and enterprise security review decide whether a feature can ship. That single fact reshapes how ai evaluation & red teaming has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.

The workload we are most often asked to take on first is onboarding automation, usually integrated against your own product. We build the smallest thing that proves the case, put it in front of real users, and expand only what earns its keep.

Built by engineers who ship production systems, not by a practice that subcontracts the build. We hand over with runbooks, tests and a team that knows how it works, not a dependency.

The sector constraints we design around

Defining constraint
per-tenant economics and enterprise security review decide whether a feature can ship
Regulations in scope
SOC 2 · ISO 27001 · GDPR and DPDP · customer data processing agreements
Systems of record
your own product · billing and metering · customer data platform · support tooling
Where we usually start
in-product AI features

AI Evaluation & Red Teaming workloads in saas & technology

  • in-product AI features
  • usage-based metering for AI
  • support deflection
  • onboarding automation
  • churn prediction

What is included

  • Evaluation set built from your real domain
  • Adversarial prompts including injection and jailbreak attempts
  • Hallucination rate measured, not estimated
  • Bias testing where the use case warrants it
  • Regression suite wired into your CI
  • Findings report with severity and remediation

Questions from this sector

How do we price AI features?

Usually usage-based or tiered, and either way you need per-tenant cost visibility first. Flat pricing on variable inference cost is how margin disappears.

Will enterprise customers accept it?

If you can answer the security questionnaire, data handling, subprocessors, training opt-out, residency. We build so those answers are straightforward.

What is prompt injection?

An attack where instructions hidden in content the model reads, an email, a web page, an uploaded file, override your intended behaviour. It matters the moment your system processes anything a user or third party supplies.

How do you measure hallucination?

Against a labelled question set from your domain with verified answers, reported as a rate rather than an impression.

Do we need this if we use a major provider?

Yes. Provider safety training covers general misuse; it knows nothing about your specific tools, data and permissions, which is where the real risk sits.

AI Evaluation & Red Teaming in other sectors

Financial ServicesBankingInsuranceHealthcare & HospitalsPharmaceuticals & Life SciencesLegal ServicesGovernment & Public SectorTelecommunicationsDefence & AerospaceEducation & EdTech

Other capabilities for saas & technology

AI Evaluation & Red Teaming for saas & technology, worth a conversation?

Tell us the workload and the regulation it sits under. We will tell you what is realistic.

Talk to an engineerWhatsApp us

Or email bd@dtrasglobal.com · call +91 74118 77878