HumainOps

AI agent operations for growing teams

Turn messy internal work into human-approved AI workflows.

We design and ship AI agents that connect to your tools, remember your process, follow approval rules, and report measurable business impact.

Book a workflow audit See what we build
Workflow audit MCP integrations Human approval gates ROI reporting
The wedge

Your team does not need another chatbot.

The real bottleneck is operational drag: copying data between tools, triaging tickets, chasing updates, creating reports, reviewing routine work, and re-explaining context every week.

We convert those repeatable workflows into controlled agent systems that act inside your existing stack instead of adding another app to check.

Offers

Packaged services that move from diagnosis to production.

Each engagement ends with a working artifact: a map, a prototype, a deployed workflow, or an operating cadence your team can keep using.

01

Agent Opportunity Audit

Map workflows, rank automation candidates, estimate savings, and identify integration and security constraints.

1-2 weeks
02

Prototype Sprint

Ship one focused agent for support, ops, sales, engineering, reporting, or founder workflows.

2-4 weeks
03

Agent Operating System

Build the production layer: tools, memory, routines, permissions, evaluation sets, observability, and team training.

1-3 months
04

Optimization Retainer

Maintain workflows, improve prompts and evals, add integrations, monitor drift, and keep agents aligned with the business.

Monthly
High-conversion use cases

Start where the pain is already visible.

Support triage

Classify tickets, draft replies, pull account context, escalate edge cases.

Sales follow-up

Summarize calls, update CRM fields, draft next steps, detect stalled deals.

Engineering ops

Review PRs, groom issues, track docs drift, run deploy verification checks.

Executive workflow

Prepare briefs, monitor inbox, synthesize updates, route decisions.

Method

Agents need operating discipline, not magic prompts.

We combine agent architecture with the boring parts that make automation reliable enough for real teams.

  1. Define success

    Baseline the workflow, target measurable outcomes, and define failure cases.

  2. Connect the tools

    Use APIs, MCP servers, or lightweight scripts so agents act on live systems.

  3. Encode memory

    Capture procedures, preferences, examples, and business rules as durable context.

  4. Add control gates

    Route risky actions through human approval, logging, and permission boundaries.

  5. Measure and iterate

    Track quality, savings, cycle time, adoption, and edge cases after launch.

ROI lens

Estimate the cost of one repetitive workflow.

Most teams can find a first workflow worth automating in under an hour. Start with time saved, then add quality, speed, and missed-opportunity gains.

Annual workflow cost $117,000
Why now

The stack is finally ready for practical agent work.

Models can use tools.

Modern models can inspect context, call APIs, run code, and recover from errors.

Connectors are becoming standard.

MCP and similar protocols make internal systems reachable without bespoke glue every time.

Teams need operators.

The market has enough AI demos. Companies need people who can turn demos into operating cadence.

First step

Book a workflow audit for one workflow your team already feels.

Bring a workflow that costs time every week. We will map the current process, identify the agent architecture, and define the fastest path to a working pilot.