AI behind the detection plane. Tuned to your environment.
AI-augmented detection runs against your traffic, your identity, and your application telemetry, with the evaluation harness that proves it works.
Model selection from BTA's 8-model catalog, RAG-tuning or inference path, configured agentic workflow patterns, and a measurement harness that runs against representative customer data before any production cutover.
Where vendor AI detection falls short.
Most detection vendors ship a model and a dashboard. What customers actually need is a model selection process, a tuning path against their data, and a measured baseline to operate against.
- Risk 01
Generic models miss your environment
Detection models tuned on internet-scale data fire on patterns that look anomalous in general but are normal for your traffic. Tuning against representative data is what changes the false-positive rate.
- Risk 02
No measured baseline before production
When the model is the detection logic, the eval harness is the spec. Without measured thresholds defined before cutover, there is no way to tell whether the detector is operating correctly.
- Risk 03
Agentic workflows act without authority
AI-driven detection that takes actions (block, isolate, ticket) needs a documented authority matrix. Otherwise the agent makes decisions that should sit with humans.
How BTA delivers AI-driven detection.
- 01
Model selection from catalog
Phase 2: select from BTA's 8-model catalog mapped to detection use case classes. Down-select against representative customer data.
- 02
Tuning path execution
RAG-tune or inference path. Tuned model artifact produced against customer data in the BTA AI POD lab.
- 03
Agentic pattern config
One of 6 agentic workflow patterns configured with documented agent-authority matrix. Pre-built evaluation harness run with metrics.
- 04
Customer-environment PoV
Phase 3A: tuned model deployed in customer environment. Eval harness runs against customer data. Measured outcomes brief signed before any production commitment.
What AI-Driven Detection delivers.
Concrete, customer-side results we measure to.
- 8Models in BTA's catalog
- MeasuredOutcomes vs Phase 2 thresholds
- SignedAgent-authority matrix
- TunedOn customer data, not generic
We're architects who execute.
Three principles every BTA engagement runs on. Visible in the work itself.
We architect, deploy, and stay through Day-2.
Every engagement is end-to-end. We design the target environment, deploy it in stages, and remain on hand through the operational handoff.
We train your team to own the outcome.
Training is part of every engagement. By the close of an engagement, your operators can run, maintain, and defend the system to an auditor.
We measure success when your team runs it alone.
An engagement closes when your team is operating the solution without us in the room. SIMPLE methodology enforces this exit criterion on every project.
We meet you where you are.
Some teams want the full BTA delivery from architecture to handoff. Others bring us in for a single advisory window or a fully managed operations contract. Pick the model that fits and adjust as the business changes.
Consulting & Advisory
Strategy and senior guidance. Architecture reviews, technology assessments, and roadmap design for teams that own their own operations.
Learn moreManaged Services
BTA runs the system day to day under your governance. Monitoring, change management, escalation paths, and SLAs for teams without Day-2 capacity.
Learn moreDeployment
Implementation-only engagement. Faster than the Full Service Lifecycle when the customer team will not own operations afterwards.
Learn moreOptimization
Refresh and refine an existing environment. Performance, automation, and refactor work for platforms already in production.
Learn moreEnablement
SIMPLE-driven Quickstart programs that deliver a specific Cisco capability into production on a known timeline.
Learn moreMentoring
Capability transfer for teams adopting a new platform. Pair-programming, custom training modules, and Cisco MINT-aligned curriculum.
Learn more
Questions buyers ask about AI-Driven Detection.
Direct answers from BTA architects who run these engagements.
What models does BTA use?
BTA maintains an 8-model catalog spanning RAG-tune and inference paths across three use case classes. Selection happens during Phase 2 against representative customer data, with the choice documented in a Model Selection Brief.How do you measure that detection actually works?
Phase 2 ships a pre-built evaluation harness with thresholds defined at Phase 1 exit. Phase 3A reuses the same harness against customer data in the customer's own environment. The same metrics, same thresholds, same harness.What is an agentic workflow pattern?
A reusable pattern for how an AI agent takes actions: which inputs trigger which decisions, which actions need human-in-the-loop, where the kill-switch sits, and which authority is required to approve each class of action. BTA ships 6 patterns; one is configured per engagement.Can this run alongside our existing XDR / SIEM?
Yes. AI-driven detection is built to enrich, not replace, XDR and SIEM. The detection plane stays where it is; the AI tuning, evaluation, and governance layer run alongside under BTA's engagement model.
Schedule a call. We’ll scope it in 30 minutes.
Bring your hardest architecture problem. We’ll tell you what we’d do, what it costs, and how long it takes.
- 30-minute scoping call
- 1,000+ projects shipped
- Training in every engagement