Automate

AI Integration & Workflow Automation

Less manual work. More leverage.

We build AI integrations, voice assistants, and workflow automation that connect to your systems and eliminate the work your team shouldn't be doing by hand.

Tell us what you want to automate

The Problem

AI adoption has a middle-market gap.

Across the 1,993 respondents to McKinsey's State of AI survey, fielded in mid 2025, 88% said their organization regularly uses AI in at least one business function. Most small and mid-sized businesses haven't, and the market isn't making it easy.

Published agency rate cards for enterprise AI work start around $60,000 and run past $150,000. Off-the-shelf "AI-powered" tools give you a chatbot wrapper with no access to your actual data. Businesses either overpay for capability they don't fully need, or bolt on generic tools that don't integrate with how they actually operate.

AI is useful when it's connected to your systems, grounded in your data, and built into the workflows your team already uses. That's what we build.

Not sure if you need AI? See what a custom build looks like first

What We Automate

AI and automation built into how you work.

AI That Works With Your Data

Generic language models know nothing about your business. We build integrations that connect models to your databases, documents, and internal systems. This is retrieval-augmented generation (RAG): your data stays where it is, the model pulls what it needs at query time. Answers are grounded in your information, not the model's best guess.

No fine-tuning required. No data migration. No vendor lock-in. The RAG market is projected to grow from $1.2 billion to $11 billion by 2030.

Streaming Interfaces

AI responses that appear in real time reduce perceived wait times, let users course-correct mid-response, and make longer outputs usable instead of frustrating. We build streaming into every AI-facing interface.

Whether it's a customer-facing chat, an internal research tool, or a code generation platform, the output arrives as it's generated. No loading spinners. No waiting for a wall of text.

Voice AI Assistants

Real-time, bidirectional audio. Not a recording that gets transcribed and emailed back an hour later. Our voice assistants handle live conversations with tool use mid-sentence: checking calendars, booking appointments, pulling records, confirming details.

Production-grade guardrails keep the assistant on task and prevent it from making commitments it can't keep. Where voice AI pays off, and where it doesn't.

Workflow Automation

Not every automation needs AI. Some processes just need the right system connecting the right data at the right time. We build automated pipelines that replace copy-paste workflows, manual data entry, and the five spreadsheets holding your operations together.

Notifications, routing, reporting, document generation. If your team does it the same way every time, it should run itself. When the steps genuinely can't be known in advance, that's where an AI agent earns its complexity.

Case Studies

What We've Shipped

SaaS Platform

Streaming AI code generator

A SaaS platform serving a global user base across seven languages. Real-time streaming output, tiered subscription plans, and multi-currency payments. Built end to end: front-end, back-end API, billing, authentication, and deployment infrastructure.

Outcome

Concept to production with paying subscribers across multiple countries.

LLM Streaming SaaS i18n Payments
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Voice AI

Voice AI scheduling assistant

Bidirectional audio streaming with mid-conversation tool use. The assistant checks availability, books appointments, and confirms details without putting the caller on hold or handing off to a human.

Outcome

Production-grade prototype with calendar integration and conversation guardrails.

Voice AI Real-Time Audio Calendar Guardrails
Internal Platform

Unified operations platform

A company ran hiring, delivery logistics, payroll, and tax reporting across five disconnected tools. We replaced all of them with a single platform. The automation layer handles routing, notifications, and report generation that used to take hours of manual work each week.

Outcome

Five tools became one. Hours of daily manual data entry dropped to minutes.

Automation Multi-Module Reporting Integration
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Working on something similar?

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When to Automate

AI is not always the answer.

If your process is unclear, changes weekly, or hasn't been done manually enough times to understand the edge cases, automating it locks in the chaos. We start by understanding the workflow. If it's stable and repeatable, automation gives your team leverage. If it's still in flux, we recommend getting the process right first.

Not every integration needs a custom model, either. Sometimes the right answer is a well-structured prompt with good retrieval. Sometimes it's a rule-based system that doesn't involve AI at all. We recommend the approach that fits the problem, not the one that sounds most impressive.

Need the custom build first? See our development services

How We Work

From workflow to working software.

  1. 01

    Map the workflow.

    What's manual today? Where does data move between systems? Where do errors or delays happen?

  2. 02

    Identify the highest-value target.

    Not everything needs automating at once. We start with the process that costs the most time or creates the most errors.

  3. 03

    Build a working version fast.

    You test real software within weeks, not a slide deck at month three.

  4. 04

    Integrate and expand.

    Once the first automation is running, we connect adjacent workflows and add intelligence where it helps.

You see working output early. Each round of feedback shapes what comes next.

How we keep it running after launch

FAQ

Frequently Asked Questions

Ask us something else
Q1

Do I need a large dataset to use AI?

No. Most integrations we build use retrieval, not training. If your data lives in a database, a CMS, or organized files, that's enough to start. We connect the model to your existing information rather than building a new dataset from scratch.

Q2

How long does an AI integration take?

A focused integration (connecting a model to your data with a conversational interface) typically ships in four to six weeks. Voice AI and multi-system automations sit closer to eight to twelve weeks depending on the number of integrations and the complexity of the workflow.

Q3

Will this work with our existing systems?

Yes. We build integrations that connect to what you already use: APIs, databases, third-party services. The goal is to add capability without replacing your infrastructure.

Q4

What happens when a better AI model comes out?

We build model-agnostic. Your system isn't locked to one provider. When a better model ships, or a cheaper one matches the quality bar on a high-volume task, swapping it in is a configuration change, not a rebuild.

Q5

How much does AI integration cost?

It depends on scope. A RAG-powered chat interface is a different project than a voice assistant with real-time scheduling. We scope every project individually, and you get a clear estimate before work starts. Most projects fall well below what enterprise AI agencies charge for comparable capability.

Q6

What if we're not sure where AI fits?

Tell us what's slowing your team down. We identify where automation or AI would have the highest impact and scope a first project from there. If AI isn't the right answer, we tell you.

Have a process you want to automate?

Tell us what's slowing your team down. We respond within one business day with questions and a rough scope.

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