Your Systems Are Already Doing Half This Work. AI Can Do the Rest.

We build agentic AI workflows that connect to the tools your team already uses and automate the processes they are still running manually.

 

$3K

per month down to

$50

per month. Running in production.

Data Adjudication System Replacement

A client in the data aggregation and adjudication space was running a purpose-built legacy system to handle their core processing work. The system cost over $3,000 a month to operate and required ongoing developer involvement for any change to the logic.

ManagePoint replaced it with a multi-agent AI architecture. Multiple agents work in sequence: ingesting source data, executing the adjudication logic, producing baseline analysis outputs, and formatting results for delivery. The system runs on current general AI platforms with no proprietary infrastructure and no vendor lock-in.

Monthly operating cost dropped to under $50. The client’s team maintains the logic themselves. When the rules change, they update the workflow. No ticket raised, no developer involved, no wait.

What We Build

Every workflow we build starts with a thorough understanding of the process it is replacing or augmenting. These are the categories we work in most often.

Multi-Agent Data Pipelines

Multiple AI agents working in sequence to ingest, process, validate, and output data. Replaces manual review chains and legacy processing systems.

Marketing Report Automation

Connects to HubSpot, Klaviyo, Shopify, Google Analytics, Meta, and more to produce one consistent monthly report. No manual assembly.

Task Aggregation

A platform-agnostic layer that sits across your CRM, project management tools, and personal workspace to surface everything outstanding in one view.

Document Processing

Extraction, classification, formatting, and routing of documents at volume. Replaces manual document handling without sacrificing accuracy or auditability.

Internal Knowledge RAG

Retrieval-augmented generation systems that let staff query internal documentation in plain language. Faster onboarding, fewer interruptions to senior staff.

Custom Integrations

When the off-the-shelf connectors do not go far enough. We build direct API integrations so AI workflows read and write to the systems that actually run your business.

MCP Tool Connections

Model Context Protocol lets your AI workflows connect directly to the platforms your team already runs. HubSpot, Microsoft 365, Slack, your CRM – we configure and deploy MCP servers so agents have live access to the tools that hold your business data, without manual exports or brittle API workarounds.

Built to Hand Off

Every workflow we deliver is designed to be owned and operated by your team after we hand it off. No ongoing developer dependency, no black box.

01

Process Audit

We map the process as it actually runs before deciding what AI should touch.

02

Workflow Design

Agent roles, data flows, error handling, and integration points are defined before we write a line of code.

03

Build and Test

Built against real data, tested against edge cases, and validated against the original process outputs before deployment.

04

Handoff and Documentation

Your team receives documentation and a working knowledge transfer so they can maintain and extend without coming back to us.

Common Questions

Answers to what we hear most often from businesses looking at agentic AI for the first time.

Basic automation follows a fixed script. If something unexpected happens, it fails or stalls. An agentic workflow uses AI agents that can reason through a task, make decisions based on the data they encounter, and adapt when conditions change. Where a traditional automation might stop if a document comes in with an unusual format, an agent can figure out what to do with it and keep moving. The practical difference is that agentic systems handle the messy, variable work that scripted automation cannot.

No. Most of the workflows we build connect directly to the tools you already use. HubSpot, Microsoft 365, Google Workspace, your CRM, your accounting software – we build integrations to these rather than asking you to move off them. In most cases your team keeps working in the same tools they know, and the AI handles what happens behind the scenes.

It depends on the complexity of the process and how many systems are involved. A focused single-process workflow can go from scoping to deployment in two to four weeks. A multi-agent system that spans several tools and handles exception logic will take longer. We scope every engagement individually and give you a timeline before work starts, not after.

We design for it. Every workflow we build includes validation steps, error handling logic, and clear escalation paths for cases the AI should not handle on its own. We also build against real data during testing rather than synthetic examples, so the edge cases that exist in your actual operation get addressed before deployment, not after.

That is the goal. We build for handoff from day one. The documentation we provide covers how the workflow is structured, what each step does, and how to make common changes without developer involvement. The $3K to $50 client we mention on this page manages their own system. When the adjudication rules change, they update the workflow themselves. That is the standard we hold ourselves to.

Tell us the process. We’ll tell you if AI can take it over.

Most businesses have at least one process that is eating hours every week and has never been looked at as an automation candidate. Book a call and walk us through it. We will be direct about whether it is a good fit and what building it would actually involve.

Platform-agnostic builds, no vendor lock-in

Designed for client-side operation after handoff

Built on real software development fundamentals

Microsoft Partner, Claude by Anthropic