Agentic AI

AI agent development that builds agents and copilots to move the needle

Reimagine your operations with custom AI agent development that automates workflows, connects your tools, and delivers measurable efficiency while optimizing costs.

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What we build

Types of AI agents we build

From workflow automation to multi-agent orchestration — agents designed for your systems, data, and guardrails.

Our process

Our process for building AI agents

Four connected phases from discovery to production — tap a stage to see what ships.

  1. 01
  2. 02
  3. 03
  4. 04
Why Xorora

Six reasons teams ship agents with us

Not another demo factory. We stay through production, support, and the handoff that leaves your team running the system.

03Included after launch

60 days of free tech support after launch

After go-live, our team stays available for 60 days to fix issues and make sure your team is confident using the system.

  • 01

    We build for production, not just demos

    Many vendors ship a proof of concept and disappear. Every agent we deliver is tested, integrated, and production-ready before handoff.

  • 02

    End-to-end AI agent development

    We handle the full lifecycle in-house: strategy, data integration, deployment, and maintenance. One team, no handoff gaps, no finger-pointing.

  • 04

    Coaching and knowledge transfer

    We don't hand over a black box. We run coaching sessions so your team understands how the system works and can flag issues early.

  • 05

    Transparent communication throughout

    You get full visibility into every stage, from the first data audit to final deployment. No surprises, no scope creep without your approval.

  • 06

    Built around your business goals

    We start by defining what success looks like for your business, not just what's technically achievable, and tie every decision back to your goals.

Production readiness

The five pillars that decide whether your agent ships

Getting an agent to a demo is easy. Getting it to production means solving all five.

01

Governance

What the agent is for, who owns it, and which regulations apply.

02

Security

Who the agent acts for, what it's allowed to do, and its audit trails.

03

Operations

How the agent is monitored, improved, and fully transitioned to your team.

04

Architecture

How the agent works inside your systems without disrupting existing workflows.

05

Data

Which data the agent can access, where it lives, and the rules it has to follow.

Find out which production pillar is blocking you.

Industries

Real-world AI agent solutions across your industry

We build AI agents for teams across sectors, tuned to the data, decisions, and rules each one runs on.

Healthcare

Use AI agents to improve patient outcomes, reduce operational costs, and support clinical teams with faster, more accurate data processing and decision support — within HIPAA-aligned guardrails.

Explore Healthcare
Example agent use cases
  • Readmission prediction and early-warning agents
  • Medical billing and claims fraud detection
  • EHR data processing and summarization
  • Hospital resource and bed-management agents

Team up with Xorora to build your AI agent

Tech & tools

Technology stack we use for developing AI agent solutions

Vendor-neutral across frontier models, open-weight alternatives, frameworks, and the clouds your teams already trust.

Frontier models

  • OpenAI logoOpenAI
  • Anthropic logoAnthropic
  • Google Gemini logoGoogle Gemini
  • Grok logoGrok

Open-weight models

  • Qwen logoQwen
  • Mistral logoMistral
  • DeepSeek logoDeepSeek
  • Llama logoLlama

Frameworks and tooling

  • LangChain logoLangChain
  • PyTorch logoPyTorch
  • LiveKit logoLiveKit

Cloud platforms

  • AWS logoAWS
  • Azure logoAzure
  • Google Cloud logoGoogle Cloud
Featured work

AI agent development case studies

Agents and copilots that reached production — one study at a time.

1 / 7

Case study carousel, slide 1 of 7

app.xorora.com
Legacy TMS Modernized for Real-Time Freight Visibility case study

Logistics · Application Modernization · Discovery Workshop

Legacy TMS Modernized for Real-Time Freight Visibility

A mid-sized freight carrier ran its core TMS on a codebase that predated the smartphone era. Phased modernization extracted modules behind clean APIs while live shipments kept moving — closing the gap between batch EDI cycles and the real-time visibility shippers now expect.

Freight cost reduction
15–30%
Fewer delivery delays
40–50%
Carrier integration timeline
Months → weeks
app.xorora.com
Modernizing Compliance Without Slowing the Business case study

Fintech · AI Consulting · AI Agent Development

Modernizing Compliance Without Slowing the Business

A mid-sized fintech lender was expanding into new states faster than its compliance team could keep up. An AI agent and custom compliance application replaced manual, state-by-state loan review with automated screening built for fair lending and audit readiness.

Review time reduction
Up to 80%
Less audit prep time
50–70%
app.xorora.com
Cutting Clinical Documentation Time with an AI Agent case study

Healthcare · AI Agent Development · AI Consulting

Cutting Clinical Documentation Time with an AI Agent

A multi-specialty medical group watched physicians spend nearly 28 hours a week on administrative work. An ambient AI documentation agent — built with clinician oversight and EHR integration at the center — reduced administrative burden without compromising note accuracy.

Documentation time saved per shift
15–30 min
Less time composing notes
8–15%
Drop in reported burnout
31%
app.xorora.com
AI-Assisted Maintenance Triage for a Multifamily Portfolio case study

Real Estate · AI Agent Development · AI Consulting

AI-Assisted Maintenance Triage for a Multifamily Portfolio

A multifamily operator was losing residents' trust one late-night phone call at a time — roughly 65% of maintenance calls came after hours. An AI agent for intake and triage cut after-hours escalations and sped up emergency response.

Faster emergency response
40–50%
Fewer emergency escalations
30–40%
Faster work-order resolution
~30%
app.xorora.com
One-Size-Fits-All Learning, Retired case study

Edtech · ML & Data Science · Discovery Workshop

One-Size-Fits-All Learning, Retired

An online learning provider watched completion rates stall even as enrollment grew — every learner moved through the same fixed sequence. A discovery-led adaptive platform replaced fixed curriculum with real-time, mastery-based pathways without losing instructor oversight.

Students reporting higher motivation
75% vs 30%
Assessment performance & satisfaction
Higher completion
app.xorora.com
From Spreadsheet Chaos to a Real SaaS Platform case study

Startups · MVP Development · Discovery Workshop

From Spreadsheet Chaos to a Real SaaS Platform

A two-person founding team had proven demand for a B2B scheduling service delivered entirely by hand through spreadsheets and email. A scoped, discovery-led MVP turned that validated manual process into a lean SaaS platform — without the scope creep that stalls most first builds.

Properly scoped MVP timeline
8–12 weeks
Of features that deliver most value
~20%
app.xorora.com
Recovering Direct Bookings from OTA Dependence case study

Travel & Hospitality · AI Consulting · AI Agent Development

Recovering Direct Bookings from OTA Dependence

An independent boutique hotel filled rooms reliably — but most revenue arrived through OTAs, with commissions eating a significant share of every booking. An AI-enriched guest data system and personalized outreach agent helped win back direct bookings from OTA-acquired guests.

Past guests converting direct
~15%
Healthy direct booking share
30–50%
Typical OTA commission range
15–30%
Good to know

Frequently asked questions

AI agents are software that can take actions toward a goal, not just answer questions. They connect to your tools, follow rules you set, and handle multi-step work like processing an invoice or resolving a ticket end to end. The useful ones run reliably in production, not just in a demo.

Ready to bring your idea into reality?

Tell us what you want an agent to do. We'll come back with a clear first step.