Most AI agencies still wire GPT into Zapier workflows and call it agentic. Codeora Vision is an AI agent development company building agent-native systems on LangGraph, MCP, and Claude. We serve B2B SaaS, DTC brands, healthcare, real estate, legal, property management, and ecommerce. Production-grade from day one. Per McKinsey's January 2025 Superagency in the Workplace report, 92% of companies are scaling AI investment and 1% reach maturity. We build for the 1%. Headquartered in Dallas, Texas.
Trusted by a top-5 US dental DSO, a Fortune 500 American precision-parts manufacturer, and a national multi-state property management firm.
INTEGRATIONS & PARTNERS
Production deployments built on the agent-native stack.
The retrofit pattern is everywhere. An AI automation agency drops a GPT call inside a Zapier workflow, adds three conditional branches, names it "agentic," and ships. The system fails at conditional #4. Hallucination control is a regex filter. Tool reliability depends on whichever integration partner shipped a stable API last week. Production observability? It doesn't exist.
MCKINSEY · JANUARY 2025
Per McKinsey's January 2025 Superagency in the Workplace report, 92% of companies are scaling AI investment BUT only 1% reach maturity. The 99% gap is where retrofitted GPT-into-Zapier stalls.
We build for the 1%. Our deployments survive branching logic past 12 conditionals because LangGraph state graphs treat branching as the primary work, not the exception. Hallucination control runs through evals — not regex. MCP handles tool connection at the protocol layer, with traceable token-by-token observability through LangSmith.
For a national multi-state property management firm running 200+ doors per region, the retrofit-to-agent-native rebuild took 90 days.
SCALE
doors managed per region
MISSED CALLS
after-hours emergency dispatches missed
MONTHLY COST
per location, flat-rate (was per-minute)
NEXT STEP
We start every engagement with a 30-minute architecture review. You walk us through your current state — eval baseline, integrations, branching complexity — and we map the rebuild path on LangGraph, MCP, and Claude. Under NDA from minute one.
WHAT WE BUILD
Each service has its own page with deployment architecture, named integrations, pricing, and vertical case studies.
AI receptionists answer every inbound call 24/7 with under-5-second pickup, integrated with Vapi, Twilio, HubSpot, and Calendly. Replaces traditional per-minute answering services (industry-standard pricing of $0.85–$1.50/minute) with a flat-rate system that books, triages, and escalates.
Always-On · Multilingual · CRM-Synced
AI ReceptionistOutbound and inbound voice agents built on Vapi, Retell AI, and Twilio with ElevenLabs and Deepgram for synthesis and transcription. TCPA-compliant call handling, real-time CRM sync, and human-in-the-loop escalation.
Vapi · Retell · Twilio
AI Voice AgentsWeb, WhatsApp, and SMS chatbots integrated with Gorgias, Zendesk, Intercom, and Shopify. Per Klarna's published 2024 customer service AI benchmark, their system reaches 80%+ autonomous resolution. Our DTC deployments target the same benchmark.
Web · WhatsApp · SMS
AI Chatbot DevelopmentBespoke multi-agent systems for non-standard architectures, built on LangGraph state graphs with MCP tool invocation and Claude reasoning. Projects $25K–$80K with optional retainer.
LangGraph · MCP · Claude
Custom AI SolutionsAgentic workflow orchestration on n8n, LangGraph, and Temporal. Multi-step branching past Zapier's conditional limits, eval-gated handoffs, and full observability through LangSmith.
n8n · LangGraph · Temporal
Workflow AutomationPrivate LLM and RAG (Retrieval-Augmented Generation) systems on Pinecone, Weaviate, Qdrant, and pgvector with LlamaIndex orchestration. Used by mid-market clients with proprietary technical libraries.
Pinecone · Weaviate · pgvector
RAG & Knowledge SystemsAI SDR systems integrated with HubSpot, Salesforce, Apollo, and Outreach. Replaces $80K–$150K SDR salary cost with autonomous outbound that hits the National Association of Realtors' 2024 5-minute response benchmark linked to 21× conversion.
HubSpot · Salesforce · Apollo
AI SDR & Lead GenerationSTILL DECIDING
We map every engagement to the right capability — voice agents, RAG systems, AI SDR, or custom multi-agent builds. Send us your current architecture and use case, and we'll route you to the service tier that ships fastest with the highest ROI.
WHERE WE DEPLOY
Each industry carries dedicated vocabulary, named platform integrations, and a deployed track record.
89% intake autonomy on Epic + athenahealth
Patient intake, prescription refills, and nurse line triage agents built on Epic, athenahealth, and Cerner — HIPAA-compliant from architecture day one.
62% reduction in no-show callbacks for top-5 US dental DSO
After-hours emergency triage, recall reactivation, and new patient intake agents integrated with Dentrix, Eaglesoft, and Open Dental.
40% → 95% phone answer rate post-deploy
Conflict-check at intake, document retrieval, and after-hours legal intake agents built on Clio, MyCase, and Filevine.
0% missed dispatches across 200+ doors per region
24/7 maintenance dispatch, rent reminders, and emergency tenant triage built on AppFolio, Yardi, and Buildium with TCPA compliance.
21× conversion at 5-min response (NAR benchmark)
5-minute lead response, listing inquiry routing, and showing scheduling agents on Follow Up Boss, KvCORE, and Chime/Lofty.
80%+ autonomous resolution (Klarna benchmark)
WISMO deflection, cart recovery, and subscription management agents on Shopify, Klaviyo, and Gorgias.
NOT A FIT?
Six verticals are where we have deployed cases. Mid-market B2B SaaS, manufacturing, insurance, and fintech are also active engagement zones. Tell us your use case and we'll either route you through our process or refer you to a better-fit partner.
DEPLOYED & SHIPPED
Every deployment tracked, measured, and shipped under NDA. Anonymized scenarios shown until client logos go live. Pick a vertical to see the architecture and outcomes.
21× lead conversion at sub-5min response. 120k+ patient intake calls per quarter. 62% reduction in no-show callbacks. DSO running 200+ locations replaced a traditional per-minute answering service across all clinics. Codeora Vision built the AI receptionist on LangGraph with Dentrix routing, Eaglesoft scheduling, and after-hours emergency triage. Eval-driven QA caught hallucinations in week 2 of training.
14× faster prescription refill workflow. 47% reduction in nurse line escalations.
12 hrs → under 2 hrs weekly doc retrieval. 100% conflict-check coverage at intake.
$1,800/mo → $599 flat-rate per location. 32% → 0% missed emergency calls in 90 days.
47% → 94% lead response rate. Under-60-second response on listing inquiries.
73% reduction in WISMO ticket volume. 4× faster customer support response.
PROOF IN CONTEXT
Branching logic, eval coverage, and observability look different for a dental DSO versus a litigation firm versus a property management portfolio. We have shipped agent-native deployments for all three. Get the architecture diagram specific to your vertical.
AGENT-NATIVE ARCHITECTURE
Retrofitted GPT-into-Zapier breaks at conditional #4. Our deployments survive past 12 because LangGraph state graphs treat branching as primary. Hallucinations are caught with evals — not regex. Tools connect through MCP at the protocol layer.
LangGraph state graphs treat branching as the primary work — deployments survive past 12 conditionals where retrofitted GPT-into-Zapier breaks at #4.
Model Context Protocol standardizes tool invocation across LLMs, replacing brittle webhooks with a clean contract that survives API churn.
Claude Sonnet 4.5 reasons over shared state with token-by-token traces through LangSmith — every decision is inspectable, not a black box.
Automated eval suites run against ground-truth datasets from week one, catching regressions before users ever see them.
REASONING & MODELS
AGENT FRAMEWORKS
INTEGRATIONS & TOOLING
INFRASTRUCTURE & COMPLIANCE
LangGraph orchestrates multi-agent state, MCP standardizes tool invocation across LLMs, and Claude reasons across the graph. Around the triad we deploy frontier models per task, vector + RAG infrastructure, and full observability through LangSmith — running on AWS or GCP with HIPAA, SOC 2, GDPR, and PCI-DSS coverage.
Agent-native architecture
A system built from the LangGraph orchestration layer up — state graphs, MCP tool invocation, evals, and observability — rather than a GPT call wrapped in Zapier. Survives production load that retrofitted workflows fail.
Multi-agent system
An architecture where multiple specialized agents coordinate through shared state (one for intake, one for routing, one for escalation). LangGraph manages the state graph. Used in our national multi-state property management deployment for 200+ doors per region.
RAG (Retrieval-Augmented Generation)
A technique that grounds LLM responses in a private knowledge base via vector retrieval. We build on Pinecone, Weaviate, and LlamaIndex. Used by a Fortune 500 manufacturer for 50,000+ technical spec queries.
Evals
Automated quality testing of AI outputs against ground-truth datasets. Catches hallucinations and regression before deployment. Runs continuously in production through LangSmith. Standard from week one in every Codeora Vision build.
TECHNICAL DEEP-DIVE
We work with teams whose CTOs run production. Get a 30-minute architecture review focused on your existing observability layer, eval framework, model selection rationale, and integration constraints. No sales pitch — just architects talking architecture.
HOW WE BUILD
A 4-phase methodology for shipping agent-native AI systems. Every engagement runs through these phases — discovery starts under NDA in week one.
Current-state diagnostic. Eval baseline. Architecture audit.
Architecture design. Model selection. RAG strategy. Compliance scope.
Build, integrate, test. Evals from day one. Human-in-the-loop fallback.
90-day calibration. Monthly evals. Quarterly model refresh.
START SMALL
The first phase of every engagement is a paid diagnostic — current-state architecture audit, eval baseline measurement, and rebuild recommendations. If the diagnostic surfaces that we are not the right fit, we route you to a better-fit partner and end the engagement there.
ENGAGEMENT TIERS
No paid pilots, no contingency contracts. A 30-minute architecture review and written scope under NDA — that's how we start.
CREDENTIALS
Clutch
Listed as an AI agent development company on Clutch.
n8n Partner Directory
Recognized partner in the n8n agent workflow ecosystem.
GitHub
Open-source contributions to LangGraph and MCP tooling.
AWS Activate
Approved for AWS Activate credits and technical partnership.
Anthropic Build Partner
Approved Claude API partner with rate-limit headroom.
HIPAA
Architecture-alignedBAAs available on healthcare and dental engagements.
SOC 2 Type II
In progressAudit logging and access controls meet SOC 2 framework.
GDPR
Architecture-alignedData sovereignty controls and DSR workflows built in.
CCPA
Architecture-alignedCalifornia user data handling per CCPA requirements.
PCI-DSS
Architecture-alignedPayment data handling via PCI-compliant gateways only.
NDA from minute one
Every engagement starts with mutual NDA before discovery.
Encryption at rest and in transit
AES-256 at rest, TLS 1.3 in transit on all client systems.
Audit logs
Every agent action and decision logged for compliance review.
Human-in-the-loop fallback
All production deployments include human-in-the-loop escalation paths.
Continuous evals
Production systems include LangSmith eval cadence with rebuild triggers.
RIGHT FIT
NOT A FIT — WE'LL ROUTE YOU ELSEWHERE
FAQ
We design and build autonomous AI systems that pursue goals across multiple tools and data sources — bespoke architectures using LangGraph for orchestration, MCP for tool invocation, and Claude or GPT-5 for reasoning. Not no-code templates.
Automation agencies wire GPT into Zapier and break at conditional #4. We build agent-native systems on LangGraph state graphs with MCP-connected tools, evals and LangSmith observability.
Architected from the agent layer up — LangGraph state graphs, MCP tool invocation, Claude reasoning, evals from week one, and observability built in. For a multi-state property firm, this meant 0% missed dispatches in 90 days.
$20K–$80K+ with optional retainer of $3K–$10K/mo. Simple 4–6 weeks, Intermediate 8–12 weeks, Complex 14–24 weeks. Every engagement begins with a 30-minute architecture review under NDA.
DALLAS, TEXAS — RESPONDING IN < 4 HOURS
Your AI initiative needs production-grade architecture, not a retrofit. Book a 30-minute architecture review. We walk through your current state, your eval baseline, and the rebuild path on LangGraph, MCP, and Claude. Discovery runs under NDA from minute one. Typical response time: under 4 business hours.