01
Workflow and data audit
A documented map of the target process, its data sources, and where an agent can act versus where it must escalate.
Agentic process automation services
An engagement that ends in a handoff, not a retainer.
A scoped path from workflow audit to a production agent your team owns and operates — every phase ends in a tangible deliverable, not a status update.
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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44% → 98% raw LLM vs guideline-executing accuracy on the open 50-scenario benchmarkHIPAA-compliant guideline-executing triage — 44% to 98% on the open 50-scenario benchmark.
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Why agentic AI
Most automation engagements end in a retainer, not an outcome.
A lot of process-automation services are structured to keep you dependent on the vendor — proprietary platforms, ongoing licensing, engineers only the vendor understands. We structure engagements the opposite way: every phase produces something you can run without us, and the engagement ends when you can.
every phase ends in something tangible
What you get
Deliverables at each phase of the engagement
Every phase produces something concrete — not a status update.
02
Working prototype and evaluation suite
A functioning agent validated against your real data, with a test suite scoring decision accuracy before production commitment.
03
Production deployment and monitoring
The agent live in your environment with observability and alerting — not a prototype left to degrade unmonitored.
04
Operator runbook and handoff
Documentation and training so your team monitors, maintains, and extends the system independently.
Delivery path
The TriStorm engagement structure
Every phase gates the next — no full commitment before the value is proven.
01
Strategize
Workflow audit, feasibility assessment, and an ROI model — a prioritised implementation plan before any build starts.
Workflow & data auditFeasibility assessmentPrioritised plan
02
Build
A working agent on your real data, with an evaluation suite and guardrails — evidence for a build decision.
Working prototypeEvaluation suiteProduction path
03
Transform
Production rollout with monitoring and governance, ending in full ownership transfer to your team.
Production deploymentMonitoring & alertingOwnership transfer
Client results
Proof from production engagements
44% → 98%raw LLM vs guideline-executing accuracy on the open 50-scenario benchmark
Guideline-executing medical triage: the LLM answers triage assessment questions; disposition follows the guideline deterministically — 98% on the open 50-scenario benchmark, on par with a 94.4% nurse-panel correct-disposition rate.
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1% → 100%share of journalist inquiries answered, manual desk vs agent
A bilingual English/Arabic autonomous agent embedded in ARIJ's Moodle environment, answering only from ARIJ's own knowledge base — across 22 countries.
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Agentic process automation services, answered
What exactly do I get from an agentic process automation engagement, deliverable by deliverable?
A workflow and data audit, a working prototype validated against your real data, a production deployment with monitoring, and an operator runbook that lets your team run the system without us. Every TriStorm phase ends in something tangible, not a status update.
Do you offer a fixed-scope engagement, or is everything custom?
Every engagement starts with the same Proof of Value structure — one process, real data, a working agent, evaluated before any production commitment. Scope beyond that follows what the Proof of Value actually finds, not a pre-sold package.
Can you take over a process automation project a previous vendor left unfinished?
Yes. We audit existing integration gaps, reasoning failures, and observability blind spots, and resolve them with your target infrastructure in mind — this does not require starting over.
What does the evaluation suite you build actually check?
Decision accuracy against known-correct outcomes, policy compliance where rules apply, and regression testing so a later change doesn't silently break something that worked. Every agent action is logged with reasoning for review.
How involved does our team need to be during the engagement?
As involved as your process knowledge requires — we need someone who understands the workflow, but we do not require dedicated engineering time from your side. We handle the build; your team validates the outcomes and receives the handoff.
What happens after the engagement ends?
You own the code, the evaluation harness, and the runbook. There is no retainer requirement — support and expansion are available if you want them, not a condition of ownership.
Start with a scoped engagement
Get a Proof of Value before any full commitment.
A 30-minute call scopes the first phase — real deliverables, evaluated before you commit further.