Solutions · Use case
Agentic Workflows.
Generative AI, scoped to the problem it solves.
Multi-step LLM agents that propose actions inside existing operational workflows.
Use-case context
Agentic workflows are the use-case most often oversold and least often deployed safely. Every vendor demo shows an agent booking flights, but the production-grade versions live inside operational workflows: exception handling, network-incident triage, provisioning. The hard problem is bounding what the agent can touch and giving every proposed action a clear human-approval surface. We build agents scoped to a specific operational workflow, with explicit tool boundaries, structured action-proposal output, and human-in-the-loop approval at every state-changing step. Tools are typed, idempotent where possible, and instrumented so every agent decision replays from logs. Measured by task-completion rate on labelled multi-step scenarios, plus a safety rate: the share of runs in which the agent stayed inside its tool boundary and produced a valid approval payload. We track time-to-resolution and operator-approval rate, so low-quality proposals stay visible. We do not deploy agentic workflows that execute state-changing actions on production systems without a logged human-approval step. The agent proposes, an operator commits, and the audit trail captures both sides. In our coverage footprint this lands first across telco, technology, logistics: the sectors where the data shapes and evaluation criteria line up cleanly with what this use-case actually measures.
How this shows up across industries
Where agentic workflows lands in production engagements.
Logistics · Generative AI Consulting
See industry →In logistics, generative AI tends to attach to exception handling, shipment-document extraction, and customer-service triage rather than core routing.
Financial Services · Custom Software Development
See industry →For financial-services clients, our custom builds tend to land in the workflow seams between core systems: onboarding, KYC enrichment, and internal-reporting tooling.
Healthcare · Custom Software Development
See industry →For healthcare clients, custom software is often the only path that meets specific clinical-workflow and integration constraints that off-the-shelf systems don't address.
Insurance · Custom Software Development
See industry →For insurers, custom software shines in claims, underwriting, and reinsurance workflows where vendor systems force compromises on logic.
Energy · Custom Software Development
See industry →For energy clients, custom software addresses operational and compliance workflows that vendor packages oversimplify.
Data shape
Operational runbooks, workflow definitions, the typed tool catalogue exposed to the agent, historical incident or exception traces, and the existing ticketing or workflow engine the agent must integrate with.
Delivering services
Where it lands first
Industries where agentic workflows applies.
- 01
Telco
Generative AI for customer-care deflection, network-incident summarisation, and provisioning workflows.
- 02
Technology
Generative AI inside the product, the codebase, and the internal tooling. Built by engineers, for engineers.
- 03
Logistics
Generative AI for exception handling, document extraction, and customer-comms across TMS / WMS surfaces.
- 04
Education
Generative AI for curriculum drafting, accessibility tooling, and administrative automation. Under explicit student-data residency.
Where we draw the line
We do not deploy agentic workflows that execute state-changing actions on production systems without a logged human-approval step. The agent proposes, an operator commits, and the audit trail captures both sides.
Talk to us about a agentic workflows engagement
A 30-minute call to scope where agentic workflows moves the curve against your evaluation criteria.
Book strategy callWhy work with Veso AI on agentic workflows
Measured
Evaluation, not opinion
Measured by task-completion rate on labelled multi-step scenarios, plus a safety rate: the share of runs in which the agent stayed inside its tool boundary and produced a valid approval payload. We track time-to-resolution and operator-approval rate, so low-quality proposals stay visible.
Proven
Quality you can measure
In the first two weeks we build a labelled evaluation set with your experts, so quality is measured from day one, not hoped for.
Production
Built to operate
We hand over working software, infrastructure-as-code, and an evaluation harness your team can run and maintain.
Related use-cases
Document Intelligence
Citation-grounded retrieval and summarisation over heterogeneous document corpora.
Internal Copilots
Role-shaped copilots over internal knowledge: Confluence, runbooks, policies, code.
Structured Extraction
Schema-conformant extraction of fields, entities, and tables from messy inputs.
FAQ
Agentic Workflows: frequently asked questions
How is success measured for agentic workflows engagements?
Measured by task-completion rate on labelled multi-step scenarios, plus a safety rate: the share of runs in which the agent stayed inside its tool boundary and produced a valid approval payload. We track time-to-resolution and operator-approval rate, so low-quality proposals stay visible. The evaluation harness is part of the deliverable, not an afterthought. We build it during the engagement so your team can run it against the next prompt, model, or pipeline change without us.
Where does Veso AI NOT apply agentic workflows?
We do not deploy agentic workflows that execute state-changing actions on production systems without a logged human-approval step. The agent proposes, an operator commits, and the audit trail captures both sides. This is a deliberate trust boundary, not a capability gap. We are equipped to build the systems we decline to build, and we decline to build them because the risk-to-value ratio in those surfaces does not justify it.
Which industries does agentic workflows apply to?
In our coverage footprint, agentic workflows most commonly lands in telco, technology, logistics, education. The specific deployment shape varies by industry: data shapes, evaluation criteria, and regulators differ enough that we re-scope each engagement against the sector it lands in.
What data shape do you need to start a agentic workflows engagement?
Operational runbooks, workflow definitions, the typed tool catalogue exposed to the agent, historical incident or exception traces, and the existing ticketing or workflow engine the agent must integrate with. In the first two weeks we look at the real data (what exists, what is labelled, where it has to live) and build the plan around what is actually there, not around an assumption.
Which Veso AI services ship agentic workflows?
agentic workflows ships under our Generative AI Consulting, Custom Software Development, AI Integration Services service lines, depending on the integration surface and the build-vs-platform trade-off. Most engagements draw on more than one. The boundary between consulting, custom build, and integration is a scoping decision we make explicit during discovery.
How does a agentic workflows engagement typically start?
We spend two weeks with your leadership and operators, build an evaluation set with your subject-matter experts, and come back with a clear plan and a clear price. That evaluation set anchors every decision after it (model choice, prompt strategy, retrieval design) so quality is measurable from week one, not from go-live.
Industries where agentic workflows applies
- Telco Generative AI for customer-care deflection, network-incident summarisation, and provisioning workflows.
- Technology Generative AI inside the product, the codebase, and the internal tooling. Built by engineers, for engineers.
- Logistics Generative AI for exception handling, document extraction, and customer-comms across TMS / WMS surfaces.
- Education Generative AI for curriculum drafting, accessibility tooling, and administrative automation. Under explicit student-data residency.
Service lines that ship agentic workflows