Persistent AI agents for business

We build persistent AI agents for your business.

An agentic team that remembers every customer and case, and carries the work across voice, email, SMS and chat. We design it, build it, and hand it over with the standards to keep it running.

How a persistent agent system looks

Intakevoice · email · SMS · chatTriage agentclassify · routeRetrievalyour documentsEvalsquality gatesWorkflow agentplan · act · checkHuman reviewwhen it mattersYour systemsCRM · ERP · ticketingAgent memorycustomer · case · history · every channel
Built for
  • Enterprise security
  • HR tech
  • Healthcare alerting
  • Case management
  • Emergency response
  • Media
  • Commerce

Agentic teams we build

Agents with roles, memory and a clear line to a person.

We describe agents the way you'd describe hires: what each one does, what it remembers, and when it hands off. A team is usually two to four of these, sharing one memory of the customer and the case.

Intake agent

Does
Answers voice, email, SMS and chat. Identifies the person and the case, collects what is missing, and opens or updates the record.
Remembers
Every prior contact with that customer, on any channel.
Hands off
Anything outside its brief goes to the case agent or a person, with the full transcript.

Case agent

Does
Owns a case from open to close: follow-ups, documents, status updates and deadlines, with compliance checks built into each step.
Remembers
The whole case history, decisions made and why.
Hands off
Regulated steps and exceptions wait for a named person to approve.

Research agent

Does
Retrieves and summarizes from your documents, policies and past cases, in any language your business works in, and cites its sources.
Remembers
What it found, where, and what has changed since.
Hands off
It answers with sources; it does not make the decision.

Operations agent

Does
Updates CRM, ERP and ticketing, schedules work and triggers your existing workflows. Every action passes an eval gate first.
Remembers
What it changed in which system, so every action can be traced.
Hands off
Actions above a threshold you set need a human approval.

How we work with you

Four ways in, from a two-week assessment to a standing head of AI.

AI roadmap and first build

A two to three week assessment of where AI pays off in your business, in which order, and what it will take. You leave with a sequenced plan and the first build scoped and costed.

Pilot to production

For the demo that works on stage and is not yet trusted with customers. We add the orchestration, evals, monitoring and compliance rules it needs, then run it with your users in the loop.

MCP servers and tool integrations

Model Context Protocol servers that expose your systems and data to AI agents and assistants, with authentication, scoping and audit, so Claude, ChatGPT, Cursor and your own agents can act on your business safely.

Fractional AI leadership

CTO-level ownership of your AI roadmap, architecture standards and hiring, without the full-time hire. We mentor the team that runs it after us.

Selected work

AI built for industries where mistakes are expensive.

Client names are withheld here and shared on request.

Connected case management

One agent for every customer, across four channels

Challenge
Businesses that run on cases handle sensitive intake calls and strict compliance paperwork with small, stretched teams.
What we built
A persistent agent that handles intake and customer communication across voice, email, SMS and in-app case chat, integrated with case workflows that enforce compliance step by step.
Result
One agent that remembers every customer and every case across four channels, with compliance enforced inside the workflow. Built and ready ahead of launch.
  • Persistent agent
  • Voice · email · SMS · chat
  • Compliance workflows

Enterprise security

Critical incidents, surfaced as they happen

Challenge
Security teams were buried in incident data and could not surface what mattered fast enough.
What we built
An AI incident-intelligence platform that pulls critical incident data into one view and analyzes it as it arrives.
Result
Analysts surface and investigate critical incidents in real time instead of after the fact.
  • Multi-agent orchestration
  • RAG
  • Real-time data

HR tech

Recruiting in 26 languages

Challenge
A global recruiting business needed candidate matching and interview prep that worked across every market it hired in.
What we built
A multilingual AI recruiting platform with automated matching, interview preparation and structured candidate intelligence.
Result
One platform serving recruiters and candidates in 26 languages.
  • Multilingual retrieval
  • LangGraph
  • Evals

Emergency response

Emergency response providers run on one system

Challenge
Personal emergency response providers were running customer lifecycle and operations across disconnected tools.
What we built
A multi-tenant account management platform covering the full customer lifecycle with operational visibility for each provider.
Result
Providers manage subscribers and operations in one system built for their business.
  • Multi-tenant SaaS
  • Operations data

Media

Search inside video

Challenge
Editors could search titles and transcripts, but not what actually happens on screen.
What we built
Semantic video search on multimodal embeddings that indexes moments inside video content.
Result
Teams find the exact moment they need by describing it.
  • Multimodal embeddings
  • Vector search

Approach

Four stages. Every one ends with something you can use.

  1. 01

    Assess

    Two to three weeks inside your business. We map the work, the data and the risks, and rank where AI will change a number you care about.

  2. 02

    Design

    Architecture, data flows, guardrails and evals, designed before the first line of code so the system can be trusted in production.

  3. 03

    Build

    We ship the first version ourselves on a stack proven across every engagement, then iterate with your users in the loop.

  4. 04

    Run

    Monitoring, eval reviews and a handover plan. Your team inherits standards and documentation, not a black box.

Built on
  • LangGraph
  • LangChain
  • TypeScript
  • Python
  • React
  • PostgreSQL
  • AWS
  • GCP
  • Azure
  • Vector databases
  • Voice agents
  • Eval harnesses
  • MCP
  • and your stack

Why iMOBEAR

Run by operators who have built, scaled and sold software companies.

Operators, not advisors

Our leadership has founded and sold two software companies, one grown to a 100-person team and acquired by a global marketing services firm. We scope AI work the way an owner would: cost, upkeep, and the number it moves.

Production is the standard

Every system we ship has evals, monitoring and a handover plan. Since 2022 we have built AI platforms for clients in security, HR tech, healthcare, media and connected case management.

The architects write the code

The people who set your roadmap and architecture also build the first version. Decisions get tested against working software, not slides.

FAQ

Questions we get before the first call.

What does iMOBEAR do?

iMOBEAR builds persistent AI agents for businesses. We assess where AI will change a number your business cares about, design the system, build the first version ourselves, and hand it to your team with evals, monitoring and documentation.

What is a persistent AI agent?

An agent that keeps memory of the customer, the case and everything that has happened so far, and carries the work across channels such as voice, email, SMS and chat over days or weeks. A chatbot answers one message; a persistent agent owns the whole thread and hands off to a person when it matters.

What is an agentic AI system?

Software in which AI agents plan and carry out multi-step work, such as taking an intake call, classifying a request, retrieving the right documents and updating your systems, with quality gates and human review where the stakes call for it.

What is MCP and why would we need a server?

The Model Context Protocol is the open standard AI assistants and agents use to call tools and read data. An MCP server for your business lets Claude, ChatGPT, Cursor and your own agents look things up and take actions in your systems, with authentication, scoping and an audit trail instead of ad hoc integrations.

How does an engagement start?

Most engagements begin with a two to three week assessment. You get a sequenced roadmap and a scoped, costed first build. From there we either build it or you take the plan to your own team.

What is fractional AI leadership?

CTO-level ownership of your AI roadmap, architecture standards and hiring, on a part-time basis. It suits companies that need senior technical direction before they need a full-time executive.

Which industries do you work in?

We have built AI platforms for clients in enterprise security, HR tech, healthcare alerting, connected case management, personal emergency response, media and commerce. Regulated and high-stakes operations are where we do our best work.

Where are you based and who do you work with?

iMOBEAR is based in Telluride, Colorado, and works with enterprise and growth-stage companies across the United States.

Start a project

Tell us what you're trying to change.

We reply within one business day. Most engagements start with a two to three week assessment.

  • Based in Telluride, Colorado. Clients across the US.
  • Fractional, project and advisory engagements
  • Enterprise and growth-stage clients
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