Agentic AI Solutions

AI agents that complete multi-step work — within limits you set.

An agent plans the steps needed to reach a goal and uses approved tools to do the work. We design the permissions, approval points and checks so it stays predictable.

Who it’s forTeams with high-volume, multi-step work across several systems — such as sales operations, customer service or finance — where the rules are clear but the work is time-consuming.
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InquiryAI agentToolsSales leadCRM New requestLook up companyCompany detailsDraft for approval✓ ApprovedCreate leadRecord createdAcknowledgement sent Waiting for approval InquiryAI agentToolsSales leadCRM New requestLook up companyCompany detailsDraft for approval✓ ApprovedCreate leadRecord createdAcknowledgement sent Waiting for approval
Illustration: one agent run, step by step.

Problems this solves

  • Skilled staff spend hours moving information between systems
  • Requests wait in inboxes before anyone acts on them
  • Simple automation breaks when the work needs judgment between steps
  • There’s interest in AI but no safe way to let it act on real systems

What you receive

  • A scoped agentDesigned for one well-defined job, with the tools it may use listed explicitly.
  • Permissions and approvalsWhat the agent may do alone, what needs approval, and who approves.
  • Evaluation resultsTested against real examples from your business before launch.
  • Audit trail and monitoringEvery step and decision logged, with alerts for unusual behavior.

Typical use cases

Each project starts with an agreed way to measure success.

  • Inbound inquiry handling

    Read inquiries, research the company, draft CRM records and replies for approval.

    Measured by: response time and the share of drafts approved without changes.

  • Customer service triage

    Classify requests, gather order details and draft responses for an agent to send.

    Measured by: time to first response and escalation accuracy.

  • Finance operations

    Match invoices to purchase orders, flag mismatches and prepare approvals.

    Measured by: exceptions caught and manual touches per invoice.

How we deliver it

  1. Choose the job

    Pick one workflow with clear rules, available data and an owner who wants it.

  2. Design guardrails

    Define tools, permissions, approval points and what the agent must never do.

  3. Build and evaluate

    Build, then test against real examples and agree the quality bar.

  4. Launch and monitor

    Start with close review, then widen as results are proven.

Technologies We Work With

We build on enterprise AI services and connect to your systems through their supported APIs.

  • Azure OpenAI and Azure AI Foundry
  • Copilot Studio and Power Automate where they fit
  • Microsoft 365, Dynamics 365, Salesforce, HubSpot and other APIs
  • Evaluation, logging and monitoring tooling

Product names are trademarks of their owners. TriAxiom Tech is independent and does not hold partner status with these vendors.

Inquiry to CRMDemonstration, synthetic inquiry
Waiting for approvalTrigger: website form
  1. Inquiry receivedWebsite contact formDone 0.2s
  2. AI reads and classifiesService, region, urgencyDone 1.8s
  3. Company details addedFrom public company informationDone 2.4s
  4. CRM record draftedLead, contact and summaryDone 3.1s
  5. Sales lead reviewsApprove, edit or rejectNeeds approval
  6. Lead created and owner assignedOnly after approvalQueued
  7. Acknowledgement sentUsing your approved templateQueued
Nothing is created in the CRM or sent to the prospect until a person approves.
Demonstration

AI Inquiry-to-CRM Workflow

An agent reads a website inquiry, adds company context and drafts the CRM record. A sales lead approves before anything is created or sent.

This is a demonstration built with synthetic data. It shows the kind of work we deliver; it is not a client project or a client result.

See all demonstrations

Support and handover

How we work with you during and after the project.

  • Project communicationA named contact, a shared plan, and milestone reviews at times that suit your time zone.
  • Access and data handlingWe use accounts you create and control, least-privilege access, and remove it at the end of the work. Data stays in your environment wherever possible.
  • Code and account ownershipCode, reports, models and cloud resources are created in your tenant or repositories and belong to you.
  • Documentation and trainingWritten documentation and training sessions so your team can run and change what we build.
  • Post-launch supportA support period after go-live, with optional ongoing support and optimization.
  • Clear, separate costsOur fees are separate from software licenses, cloud consumption and advertising spend, which you pay directly to the provider.

Related services

Frequently asked questions

What’s the difference between an agent and automation?

Automation follows the same defined steps every time. An agent decides which steps to take toward a goal, using tools it’s allowed to use. Agents suit work where the path varies; automation suits work where it doesn’t.

Can an agent take actions without anyone checking?

Only the actions you approve for it. Anything consequential — creating records customers see, sending messages, moving money — can require a person’s approval.

How do you make sure it works properly?

We test the agent against real examples before launch, agree a quality bar with you, and monitor it in production.

Which AI model do you use?

We choose per use case based on quality, cost and where your data must be processed, typically through Azure OpenAI or other enterprise AI services under your own account.

Is our data used to train the AI model?

Enterprise AI services such as Azure OpenAI state that customer data isn’t used to train their models. We confirm the terms of the specific service with you during design.

Find the right first agent for your business.

Describe a multi-step process that takes up your team’s time.

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