Six things we do, and what you actually get.

Software that reads a request, works out what it means, takes action in your systems, and escalates when it shouldn't guess. That's an agent. The difference between one that earns its keep and one that becomes a liability is entirely in the boundaries around it.

We build agents with explicit tool access, no more than the task requires, plus validation on the way in and out, human approval at the points where a wrong answer is expensive, and a log that lets you reconstruct any decision the agent made and why. Multi-step workflows get orchestrated with real state handling, so a failure at step six doesn't silently leave step three half-finished.

Typical use: quote and proposal generation, customer and vendor email triage, claims and application intake, document review and extraction, research and summarization, internal knowledge assistants over your own content, tier-one support deflection.

See four of these running in production, with the architecture of each

Most companies don't have an AI problem. They have twenty candidate processes, no way to rank them, and a vendor telling them all twenty are urgent.

This is a fixed-scope assessment. We inventory the candidates, measure the ones that matter, score them on value, feasibility, data readiness, and risk, and hand back a sequenced roadmap with cost and benefit attached to each item. It includes the things that shouldn't be automated and why. That is usually the most useful page in the document, because it stops you spending money to make a broken process faster.

If you already have an internal champion, this gives them the ammunition to get funded. If you don't, it tells you whether there's enough value here to justify starting at all.

A lot of companies bought RPA between 2018 and 2022 and are now paying maintenance on bots that break every time a vendor moves a button. Some of that estate is worth saving. Some of it should be shut off, and someone needs to say so.

We audit what you have: what it does, what it costs, how often it fails, and what it actually saves. Every bot gets a recommendation: stabilize, re-platform onto something cheaper or more durable, replace with an API or an agent, or retire. Then we do the work. Screen-scraping automation replaced with a proper integration usually costs less to run and stops failing on cosmetic UI changes.

Direct experience with Automation Anywhere A360 estates, queue-based architectures, mainframe and legacy integration, credential and IAM handling, and the operational side of running bots at volume.

The unglamorous category that quietly pays for everything else. Documents that get retyped into a second system. Approvals that live in someone's inbox. Month-end reports assembled by hand from four exports. Two systems that were never designed to talk and now have to.

Often the right answer here isn't AI at all. It's an integration, a queue, and a clear owner. We'll tell you that when it's true. When AI does belong in the middle of it, usually for classification, extraction, or judgment on unstructured input, it goes in as one component of a system with proper error handling rather than as the whole architecture.

Your staff are already using AI tools. The only question is whether that's happening inside a policy or outside one. A 60-person company doesn't need an enterprise AI governance framework, but it does need answers to a short list of questions before something goes wrong.

Who may deploy an agent. What data it may touch, and what may never be pasted into a third-party model. How output gets reviewed before it reaches a customer. What's logged and retained. Who is accountable when the answer is wrong. What happens to access when someone leaves. We write policy that fits how your company actually operates, then set up the intake and review process that makes it stick.

Built on enterprise Center of Excellence experience covering intake, pipeline management, standards, security review, and benefit reporting, scaled to the size of the organization rather than copied from one ten times larger.

Automation is not a project you finish. It's a system somebody has to run. Processes change, vendors change their APIs, models get deprecated, volumes shift, and exception patterns drift.

We'll run it for you, or stand behind whoever on your team now owns it. Either way you get monitoring with real alerting, an exception queue somebody watches, scheduled tuning as behavior drifts, change management when an upstream system moves, and a monthly report showing what it processed, what it saved, and where it failed.

Retainer-based. Cancellable. And because everything is documented and handed over, leaving doesn't cost you the system.