DALLAS, TEXAS · AGENT-NATIVE AI DEVELOPMENT

Most AI Agents Never Reach Production. We Build the Ones That Do.

Codeora Vision is an AI agent development company in Dallas, Texas, built on one conviction: most AI stalls because it is retrofitted onto tools that were never designed to reason. The company builds agent-native systems on LangGraph, MCP, and Claude that plan, act, and write back to the stack a business already runs. Seven productized systems span six verticals for clients across the US, UK, EU, Canada, and Australia, each shipped to production and calibrated against real traffic. Agent-native, not retrofitted.

LangGraphMCPClaudeLangSmithSOC 2HIPAA

Updated July 21, 2026

CODEORA VISION AT A GLANCE

HEADQUARTERS

Dallas, Texas

SERVES

US · UK · EU · Canada · Australia

BUILT ON

LangGraph · MCP · Claude

CATALOG

7 productized AI systems

VERTICALS

Healthcare · Dental · Legal · Property · Real Estate · Ecommerce

STANDARDS

SOC 2 · HIPAA · TCPA · GDPR

THE MARKET MOMENT

The gap we were built for

The distance between AI ambition and AI in production has never been wider. Capgemini projects agentic AI could unlock 450 billion dollars in value by 2028, yet only 2 percent of organizations have scaled agents so far. We built Codeora Vision for exactly that gap.

95%

of enterprise GenAI pilots show no measurable P&L return

MIT NANDA · 2025

1%

of companies have reached AI maturity

McKINSEY · JAN 2025

33%

of enterprise software will embed agentic AI by 2028, up from under 1% in 2024

GARTNER · 2025

40%+

of agentic AI projects will be canceled by the end of 2027

GARTNER · 2025

OUR THESIS

Why do most AI agents never reach production?

Because they are retrofitted. Most builds bolt a language model onto a linear automation like Zapier, or dress a chat widget as an agent, then hope it holds under load. It does not. Codeora Vision builds agent-native systems on LangGraph and MCP, where the agent plans, branches, calls tools, and recovers from failure as a designed capability, not a patch. That difference is what survives real traffic.

We start from the architecture, not the demo. A retrofitted flow looks impressive in a controlled test and then breaks at the first edge case a real customer throws at it. An agent-native graph treats branching, tool calls, memory, and escalation as first-class parts of the system, so the build that wins the demo is also the build that ships.

GARTNER · JUNE 2025

~130 real vendors

Of the thousands of vendors claiming "agentic AI," Gartner counts only about 130 as the real thing, and urges teams to "rethink workflows from the ground up."

BUYER TRANSLATION

Most of the market is agent-washing. The work that reaches production is architected from the workflow up, which is the only way Codeora Vision builds.

HOW WE BUILD

The ORACLE Build Method

Every build runs the same four-phase method. It is the discipline that moves an agent from a promising idea to a system that answers real calls and keeps improving after launch.

01

Observe

We map the workflow, the stack, and the compliance line before writing a line of code. Under NDA from the first call, with no named references required.

02

Reason

We architect the agent graph on LangGraph, MCP, and Claude, choosing the model per task rather than by vendor, and design the branching, memory, and escalation paths.

03

Architect

We build against your real integrations, HubSpot, Salesforce, Epic, Clio, AppFolio, or Shopify, test on live traffic, and instrument every step for evals.

04

Calibrate & Evolve

A 90-day calibration window, continuous monitoring through LangSmith, and retraining as patterns shift, so the system improves against real traffic instead of drifting.

THE TRACK RECORD

Built, shipped, and calibrated in production

Client names stay private by default, so every result below is described by region, size, and vertical only. Each figure reflects a single deployment and is not a guarantee of the same outcome elsewhere.

DENTAL DSO — SOUTHWEST US, 40+ LOCATIONS

[XX]%

of after-hours calls recovered and booked, previously lost to voicemail

single deployment, not a guarantee

LEGAL — MULTI-STATE PERSONAL-INJURY FIRM

< 60 sec

Intake response cut from [X hours], with conflict checks automated

single deployment, not a guarantee

PROPERTY MANAGEMENT — NATIONAL OPERATOR, 12,000+ UNITS

24/7

Tenant and maintenance calls handled, [XX]% resolved without a human

single deployment, not a guarantee

CLIO 2024 · KLARNA 2024

40% → 80%+

Only 40% of calls to law firms are answered (Clio 2024 Legal Trends Report), while production AI now resolves 80%+ of support contacts autonomously at scale (Klarna, 2024). The ceiling on most businesses is not demand, it is response. Agent-native systems close that gap where retrofitted tools stall.

OUR PRINCIPLES

Four things we will not compromise on

Production or it does not ship

A pilot that dazzles in a demo and breaks on live traffic is a failure. We ship to production or we do not ship. That standard is the whole company.

Agent-native, not retrofitted

Built on LangGraph, MCP, and Claude. We route across Claude Sonnet 4.5, Claude Opus, GPT-5, GPT-4o, Gemini 2.5, and Llama 3.3 by task, never by vendor lock-in.

Compliance is the floor

HIPAA, SOC 2, TCPA, GDPR, and PCI-DSS. Designed for audit from day one, because oversight bolted on after launch is the slower, costlier route.

Flat-rate ownership

A fixed setup and monthly fee. You own the system, the prompts, and the data. No per-minute meter, no platform lock-in, no surprise overage.

DELOITTE · 2026

21%

Only 21% of organizations have a mature governance model for agentic AI, even as adoption scales (Deloitte State of AI in the Enterprise, 2026). Governance designed in is cheaper than governance retrofitted. We build for audit from the first phase, not the last.

WHO WE SERVE

Who we build for

We work with teams that live or die by response time, from single practices to national operators, across North America, the UK, the EU, and Australia.

THE STACK

The stack behind every build

No black boxes. Every build is assembled from named, production-grade components, chosen per task and wired into the tools you already run.

MODELS

Claude Sonnet 4.5Claude OpusGPT-5GPT-4oGemini 2.5Llama 3.3

ORCHESTRATION

LangGraphMCPLangChainLangSmithn8n

VOICE & TELEPHONY

VapiTwilioTelnyx

INTEGRATIONS

HubSpotSalesforceEpicDentrixClioAppFolioShopifyGoogle Calendar

STANDARDS

SOC 2HIPAATCPAGDPRPCI-DSS

FAQ

Questions about Codeora Vision

Codeora Vision is an AI agent development company headquartered in Dallas, Texas. It builds agent-native systems on LangGraph, MCP, and Claude for teams in healthcare, dental, legal, property management, real estate, and ecommerce. The catalog spans seven productized systems, from AI receptionists to custom multi-agent workflows, each shipped to production and calibrated against real traffic rather than left as a pilot.

Codeora Vision is headquartered in Dallas, Texas, and works remote-first with clients across the United States, United Kingdom, European Union, Canada, and Australia. Delivery, scoping, and calibration run remotely, with on-site engagements available for larger enterprise builds. Data handling and compliance are scoped to each client's region, including GDPR for UK and EU deployments.

Most agencies retrofit a language model onto a linear automation or a chat widget. Codeora Vision builds agent-native, on LangGraph and MCP, so the agent plans, branches, and recovers from failure by design. Gartner expects more than 40 percent of agentic projects to be canceled by the end of 2027, most for want of real architecture. The difference is what reaches production.

Codeora Vision connects to tools like n8n, Make, and Zapier when they fit, but does not build the core agent on them. A linear automation cannot hold state, branch, or recover the way an agent graph can. The reasoning layer is engineered on LangGraph, MCP, and Claude, then wired into the existing stack through native integrations and APIs.

The client does. Codeora Vision works on flat-rate ownership: a fixed setup and monthly fee, with the client owning the system, the prompts, and the data. There is no per-minute meter and no platform lock-in. If the engagement ends, the system and its configuration stay with the client rather than disappearing behind a vendor wall.

Codeora Vision works with growing small and mid-sized businesses through to multi-location enterprises, including dental support organizations, multi-state firms, and national operators. Productized systems suit smaller teams that need a fast, fixed-price build. Custom multi-agent and RAG work suits larger organizations with deeper integration and compliance needs. The free scoping call sizes the right path.

Yes. Alongside its Dallas base, Codeora Vision serves teams across the United Kingdom, European Union, Canada, and Australia. Compliance, calling rules, and data residency are scoped per region, including GDPR for UK and EU builds. Delivery runs remotely, so location is rarely a constraint on the work.

Start with a free AI consultation. It is a 30-minute architecture review, under NDA, that maps the workflow with the fastest payback and returns a written scope, a fixed price, and a timeline. There is no obligation to build afterward, and Codeora Vision responds to new inquiries in under four business hours.

DALLAS, TEXAS — RESPONDING IN < 4 HOURS

Ready to build an agent that actually ships?

Bring us the one workflow you are tired of running by hand. We will scope an agent-native system on LangGraph, MCP, and Claude that reaches production, or tell you honestly if we are not the right fit. No retrofit, no pressure.