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Embedded AI team

We ship
AI agents inside
the stack you
already trust.

VEXUVA designs, builds, and ships custom agents for other teams — then embeds them in the website or product you already operate. Models, data, and infrastructure included. You own what we ship.

Talk to usOverview 2 MIN

Owned by you · Shipped into your product · Run on your infrastructure

  • AI agents
  • Models and ML
  • In-product embeds
  • Data and infrastructure
PRODUCT

INBOX

Refund for order 1842

Customer asked for a refund. The order is inside the 30-day window.

Thread with Acme Co.

AGENT

Draft ready in the thread

Refund approved · Send

YOUR STACK

Database · API · UI

Deployed

An agent inside the product. Not beside it.

Our customers

Teams we build with.

From email platforms and travel booking to brand studios, cafés, and AI tooling, teams bring us one workflow and keep building.

  • IceWarpEmail & collaborationBrand BridgeBrand & marketingCoffee Cup India × FitCafèFood & beverageKiroAI agent toolingRezLive TravelsTravel & reservationsEmail & collaborationBrand & marketingFood & beverageAI agent toolingTravel & reservationsEmail & collaborationBrand & marketingFood & beverageAI agent toolingTravel & reservations

What they say

Sample reviews, shown until customer-approved quotes are ready.

Sample review
“VEXUVA put an assistant inside our webmail that drafts replies from the thread. It lives where our users already work, and our support queue felt it in the first month.”
IceWarpProduct team
Sample review
“They built an agent that turns a client brief into first-round campaign concepts. Our strategists start from a strong draft now, and we own every part of the system.”
Brand BridgeStrategy team
Sample review
“Orders, loyalty, and stock now run through one agent across both brands. Store managers ask questions in plain language and get answers from live data.”
Coffee Cup India × FitCafèOperations
Sample review
“VEXUVA designed the data layer and evaluation pipeline behind our agent replays. Clean schema, a clear handoff, and infrastructure our engineers run themselves.”
KiroEngineering

Platform

What we build into your organization.

Four kinds of work. One team that stays from the first workflow through the infrastructure that runs it.

  1. 01

    AI agents for organizations

    Agents that take a defined job inside your company — support, operations, review, dispatch — with a workflow, a toolset, and an owner.

    • Workflow
    • Toolset
    • Named owner
  2. 02

    AI, ML, and agentic systems

    Models, retrieval, tools, and evaluation designed as one system. We use the smallest approach that holds up on your real tasks.

    • Models
    • Retrieval
    • Evaluation
  3. 03

    Agents inside existing products

    We inject the agent into the website or application people already use. The work stays in the workflow. There is no side portal to adopt.

    • Existing interface
    • Permissions
  4. 04

    Databases and infrastructure

    Schema, data stores, and the runtime around the agent. Designed for your environment, then handed to the team that will operate it.

    • Schema
    • Data stores
    • Runtime

Selected work

Solutions we've shipped.

Agents, models, and automation running inside real products, from travel booking to the factory floor.

  • Corporate travel

    A travel platform with an agentic layer

    • Guided organization onboarding
    • Travel policies read from uploaded documents
    • Agent-routed booking approvals
    • ML re-ranking for flights and hotels
    • Natural-language search for flights and hotels
    • A booking agent on WhatsApp
  • Manufacturing

    An AI auto-planner for production

    • Machine-level production mapping
    • Order completion prediction
  • Finance operations

    AI invoice processing

    • Data extraction
    • Validation
    • Approval routing
  • Sales and service

    AI inside the CRM

    • Account summaries
    • Drafted follow-ups
    • Record updates

Method

How we build it.

Scroll through the build. Each step adds its piece to the system, until it runs inside your cloud.

WORKFLOWAGENTMODELEVALSAGENTYOUR CLOUDDATABASESERVICES
01 / 04Scoped

  1. 01

    Scope the workflow

    We sit with the people who do the work, name the decision an agent should own, and cut anything that does not change the outcome.

    • Map the current path
    • One workflow, one owner
    • A metric you can defend

  2. 02

    Build the model or agent

    The model, the tools it can call, and the evaluations it has to pass are set before the agent touches a live queue.

    • Task-level evaluation
    • Tools your team already uses
    • Handoff when confidence drops

  3. 03

    Embed it into your product

    The agent shows up in the website or product people already open, with the same roles and permissions as the team.

    • Existing interface
    • Actions, not a side chat
    • No new place to check

  4. 04

    Deploy where your data lives

    Databases, services, and the release path are designed for your environment. Your team can run what we leave behind.

    • Your cloud and network
    • Schema and data stores
    • A handoff you can operate

Travel out to the agents.

Builder agent

Turns the workflow into a working system.

Selects the model, the data path, and the place in the product where the agent should act.

Model · data · evals · interface

Product agent

Plugs into the system you already run.

Wired into the product, data, and roles your team already uses.

Website · workflow · permissions

Deploy agent

Stays where your data already lives.

Runs in your environment, then handed to the team that will operate it.

Cloud · database · handoff

Turns the workflow into a working system.

01 / 03

Swipe to fly out to the next agent

Contact

Tell us the workflow.

Share the product, the decision an agent should own, and where the data lives. We reply with a scoped way to build it.

hello@vexuva.ai

We reply by email with a scoped way to build it.