AI Workflow Rescue & Quality Care
Fix the AI tool your team stopped trusting
An assistant that gives inconsistent answers. An automation that keeps breaking. A workflow that still needs too much checking. We review what you have, test it against real examples, and improve the parts causing trouble. Ongoing care can keep an eye on failures, output quality, and changes to connected tools.
Does this sound familiar?
- Our chatbot gave a client the wrong answer, and now staff check every reply.
- The automation breaks every few weeks, and we only find out when a customer complains.
- The person who built it has left, and nobody wants to touch it.
- We spend more time fixing the AI's drafts than we would writing them ourselves.
- It worked in the demo. It doesn't work on our real cases.
Illustrative example · Newcomer settlement nonprofit
A 20-person settlement agency added a website chatbot to answer questions about programs, eligibility and office hours in English and Arabic. Front-desk staff now double-check its answers because some are out of date.
Before
- The chatbot draws on old program pages and an expired intake guide.
- Its answer on eligibility changes depending on how the question is worded.
- Nobody sees a wrong answer unless a client mentions it.
After setup
- It answers only from a reviewed set of current documents, and staff can update that set.
- It gives the same answer to the same question and refers eligibility decisions to a caseworker.
- Flagged and unanswered questions go to a weekly review list for the program lead.
How it works
- 1
Agree what correct looks like
We write down what the tool should do, what it must never do, and a set of real test cases your team agrees on.
- 2
Test it and find the cause
We run your real examples through it and trace each failure to its source: outdated documents, weak instructions, a broken connection or the wrong tool.
- 3
Fix and retest
We repair what's causing trouble, clean up the source material, and run the same tests again so you can compare before and after.
- 4
Set up checks
We add failure alerts and a short review routine. You get written notes on how it works and how to fix common problems.
Your project can include
- Workflow diagnosis
- Source improvements
- Repairs
- Quality checks
- Alerts
- Clear handover instructions
What you bring
- Admin access to the assistant, automation or platform it runs on
- Examples of where it went wrong, with screenshots or tickets if you have them
- The documents and rules it should be working from
- Someone who knows what a correct answer looks like
What we handle
- A written diagnosis of what's failing and why
- A test set built from your real cases
- Repairs to instructions, source documents, connections and logic
- Retesting against the same cases
- Failure alerts and a simple quality check routine
- Handover notes your team can follow
What this is not
- Some tools aren't worth repairing. If a rebuild costs less, we'll say so and show you why.
- We can reduce errors, but no AI tool is right every time. We plan for that with review steps and handoffs to people.
- We review before we change anything, and we agree the fixes with you first.
Tools we often work with
We start with what you already pay for. These are common, not required.
- ChatGPT Business
- Microsoft 365 Copilot
- Copilot Studio
- Claude
- Gemini for Google Workspace
- Power Automate
- Zapier
- Make
- n8n
- Voiceflow
How we usually work on this
Start with a diagnosis and repair as Build & Hand Over. If the tool faces customers or depends on several connected systems, Build & Care keeps someone checking it after the fix.
Ways to work togetherQuestions about workflow rescue
Can you fix something another company built?
Yes. This work is often on tools someone else set up, such as a former employee or a vendor who moved on. We need admin access and whatever notes exist. If there are no notes, we work it out from the setup itself and write the documentation as we go.
How do we know it's actually fixed?
We test it on the same real examples before and after the repair. You see which cases failed, which now pass, and which still need a person. That gives you something concrete to judge, instead of taking our word that it's better.
What if it needs to be rebuilt?
Then we tell you after the diagnosis, before any repair work starts. Sometimes the tool was the wrong choice, or the setup is so tangled that fixing it costs more than starting again. You get the reasons and the options, and you decide.
How much does a review cost?
Pricing is scoped per project. We can start with the diagnosis on its own, then quote the repairs once we know what's wrong. Each proposal lists our fees and, separately, any software or AI usage costs, so nothing is bundled out of sight.
What does ongoing care include?
Ongoing care covers the workflows named in your plan. It usually includes failure alerts, a regular quality check on real outputs, and updates when a connected tool changes. The plan states what we watch, how fast we respond, and what counts as new work.
Related answers
Why your AI chatbot gives wrong answers, and how to fix it
Most wrong chatbot answers have five causes: old documents, bad retrieval, no "I don't know" rule, scope creep and vendor updates. How to fix each.
CostHow much does an AI consultant cost a small business in Canada?
What drives the cost of AI work for a Canadian small business: the build, the software, ongoing care, and what a fair proposal should spell out.
Getting startedShould you hire an AI consultant or train your own staff?
Most small teams need both: train staff on the AI in tools you already pay for, then bring in outside help for connected workflows that need testing.
Make your existing AI more dependable. Tell us where it gets stuck.
Tell us what you are working toward and what keeps getting in the way. We will help you identify a practical next step.
Start with what you want to achieve
You can describe the problem in your own words. We will work through the possibilities together.