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Device activation
Reads activation requests and provisioning data, completing device setup end to end without a person keying in every step.
Agentic AI in telecommunications
Automate activation and routing at carrier scale .
We build agents that handle device activation, call verification, and routing at volume — the same high-volume, escalation-aware coordination pattern proven in other production deployments.
Trusted by operators
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+11.76% orders from day 1 of the Australian launchThree-agent product advisor guiding customers through print-order configuration.
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Supply chain intelligence agents reducing manual coordination overhead.
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37 kernels ported from CUDA to Intel GaudiProduction AI workloads moved to new hardware for on-prem LLM deployment.
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AI agent implementation for a global automotive enterprise.
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2 hrs → 3 min to generate a workflowText-to-workflow agents building validated node graphs inside the platform.
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0 hallucinations across 329+ validation scenariosHIPAA-compliant agentic RAG over proprietary clinical triage guidelines.
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Why agentic AI
Telecom scale breaks fixed-script automation
Device activation, call verification, and routing generate volume that overwhelms manual review, but the exceptions are too varied for a fixed IVR script. An agent reads the actual request, reasons across provisioning and account systems, and completes the task end to end, escalating only genuine exceptions.
every routing decision traces to account data
Use cases
Where agents earn trust in telecom operations
High-volume workflows with a clear escalation path.
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Call verification and routing
A voice assistant verifies caller intent and routes to the right queue or resolution, handling higher volume without added headcount.
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Network exception coordination
Cross-references signals across provisioning and account systems to resolve error cases instead of routing every exception to a technician.
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Customer support with account context
Answers billing and service questions grounded in the actual customer's account and provisioning status.
What the mechanism delivers
Evaluate-and-route at volume, measured in production
The first two figures are from a telecom deployment: a US fiber operator serving 150,000+ households, where device activation ran through three support agents on the phone for every field installation. We cannot name the operator publicly. The third is Mixam, print on demand, and it is here because it measures the same evaluate-and-route mechanism at a volume no telecom workflow escapes. Every figure links to the case study behind it.
Agents do not change a subscriber's plan, credit an account, or touch network configuration on their own. They read the request, check it against the systems of record, draft the resolution, and log every step for the person who signs off.
Daily error analysis and processing, before the agent
330 min
Every field installation routed through a support center where three agents manually worked activation across multiple systems — labor cost on every job, and a bottleneck that blocked expansion into other states.
98%
Automation of device activation workflows
Routine activation work was nearly eliminated, and call-center agents were redeployed to higher-value work rather than cut.
95.4%
Success rate in workflow results
Not a telecommunications deployment — A three-agent product advisor guiding customers through print-order configuration — 15 tools working against more than a billion product combinations.
Client results
Proof from production agentic deployments
Our telecom work — 98% automation of device activation for a US fiber operator serving 150,000+ households, and an LLM voice assistant handling call verification and routing — is with clients we cannot name. These are the named studies you can read in full: the same evaluate-and-route, grounded-retrieval and staged-validation mechanisms, shipped in print on demand, media and healthcare.
Delivery path
From workflow audit to a production agent
TriStorm keeps scale and engineering aligned — integration and volume questions surfaced before full build commitment.
Map systems and workflow
We audit target processes, provisioning and CRM boundaries, and error patterns — ranking automation candidates by volume and impact.
- Systems & workflow audit
- Error-pattern review
- Prioritised use case
Build and validate the agent
We implement against real provisioning and call data shapes, with an evaluation suite scored before production rollout.
- Working prototype
- Evaluation suite
- Escalation rules
Deploy with monitoring
Production rollout with monitoring and audit logging, plus a structured handoff so your operations team runs the system independently.
- Production deployment
- Audit trail & monitoring
- Operator runbook
Not sure where to start?
A 30-minute call is usually enough to find your highest-value use case
Talk directly to our founders and PhD AI engineers. We will show you real results from 30+ agentic projects and walk through how to apply them to your own service-assurance and support workflows. Every example is something already running in production.
Independence
How we help you stay independent
Your team owns what we build. We work on open-source foundations, and the agent logic, the integrations and the evaluation harness transfer to you at the end of the engagement.
Technological sovereignty
We have delivered systems that run with no connection to a big-tech platform: sovereign AI, engineered in Europe.
Small language models
Smaller models keep token costs predictable in day-to-day operations and let the system run on your own internal or on-premise infrastructure.
Open source
We build on open-source software as contributors and as an official Pydantic implementation partner, so the stack stays inspectable and your team keeps the source.
FAQ
Agentic AI in telecommunications, answered
Where does agentic AI fit into telecom operations?
In high-volume, document-and-decision workflows — device activation, call verification and routing, and customer support that needs account context. Device activation is where we have shipped: for a US fiber operator serving 150,000+ households, an agent that ingests ticket data, device telemetry and account context now automates 98% of activation workflows, work that previously routed every field installation through three support agents on the phone.
How is this different from the IVR and automation we already run?
An IVR follows a fixed script. An agent reads the actual request or document, reasons across account and provisioning systems, and completes the task (activation, verification, routing), escalating only genuine exceptions.
Do you have telecom-specific proof, or is this adapted from other industries?
Yes, though not under a name we can print. We built an activation agent for a US fiber-powered operator serving 150,000+ households across 500+ master-planned communities: 98% automation of device activation, and daily error analysis cut from 330 minutes to 30. We also built an LLM voice assistant automating call verification and routing for a call center. Both clients are anonymized, so the studies you can read end to end are outside telecom — Mixam's three-agent advisor at a 95.4% success rate, and Schmitt-Thompson's zero-hallucination triage agent across 329+ nurse-reviewed scenarios.
Can an agent actually handle voice-based customer interactions?
Yes, when the interaction is grounded in real account data rather than a generic script. We build this with the same staged retrieval-and-validation approach behind Schmitt-Thompson's clinical-triage agent (checking the request against source data before answering) adapted to call verification and routing.
Can this integrate with our existing provisioning and CRM systems?
Yes, through your existing APIs — no rip-and-replace of your provisioning or billing infrastructure.
Do we own the system after it is built?
Yes. Full ownership of agent logic and integrations — no proprietary runtime lock-in.
Start with one workflow
Map one carrier-scale workflow worth automating
A 30-minute call identifies integration points, volume patterns, and a realistic path to a working agent.