Advise & Run · Monthly, ongoing
Your software, kept running and improving every month
Monitoring, security patches, fixes, and change requests under one monthly agreement, with response times you can count on. For systems we built, systems others built, and AI agents in production.
- Web application
- API and integrations
- Backups
- AI support agent
Requests
- Add a field to the claim formIn progress
- Framework security patchIn staging
- Re-test agent on new modelScheduled
- Monthly reportSent
Launch is the start, not the finish
The builder moved on.
The vendor or freelancer who built your system is busy, unresponsive, or gone, and nobody else knows how it works.
Small changes wait for months.
A new field, a report, a pricing rule: each one becomes a mini-project with a quote, a queue, and a delay.
AI agents drift quietly.
Models change every few months. Without regular re-testing, an assistant's answers can get worse before anyone notices.
What we do
One team that looks after your system like it's our own
We take responsibility for your software in production. We watch it, patch it, back it up, fix what breaks within agreed response times, and make the changes your business needs each month. If you run AI agents, we also monitor their answers and costs and re-test them when models change. Once a quarter we review what should be upgraded next.
- Monitoring and alerts, so we often know about a problem before your users do
- Security patches and dependency updates on a regular schedule
- Backups, with restores tested
- Fixes under an SLA with agreed response times
- A monthly allowance of change-request hours
- AI agent monitoring and re-evaluation when models change
What you get
Monitoring and alerting
Uptime, errors, and performance watched continuously by automated checks, with alerts to our team.
Security and updates
Regular patching of frameworks, libraries, and servers, with changes tested in staging first.
Backups and recovery
Scheduled backups and periodic restore tests, so a backup is known to work.
Fixes under an SLA
Issues handled by priority, within the response times in your agreement.
Change requests
A monthly block of hours for improvements, new fields, reports, and integrations.
AI agent care
Monitoring of answer quality, cost, and failed actions, with re-evaluation against real conversations when a model changes.
Monthly report and quarterly review
What we did, what we found, and what should be upgraded next.
How it works
- 11–2 weeks
Onboarding check
For systems we built, a handover check. For systems built by others, a paid Code & Architecture Audit first, so we both know what we're taking on.
- 2First weeks
Set up
Monitoring, alerts, backups, access, and a runbook for your system, plus a staging environment if there isn't one.
- 3
Agree the rules
Priorities, response times, how to raise a ticket, and how change requests are estimated and approved.
- 4
Monthly cycle
Fixes and change requests delivered through tested, staged releases, with a monthly report.
- 5
Quarterly review
Upgrades, risks, and the roadmap for the next quarter.
We already run business-critical systems every day
“We build software that runs a business process end to end, then stay to operate it.” That's how we work today.
6 years
Continuous production service, 2020 to 2026, with ongoing releases
Release history: first release October 2020, about 40 tagged releases since
33
Tagged releases of an AI support platform's backend and dashboard between January and August 2026
Release history
11
Tagged releases from May to September 2026 through staging and production pipelines, for a US client
Release history
3.96 to 4.30
Blind-graded answer quality out of 5 on 50 real customer questions after a model upgrade, with invented facts cut from 4 items to 1
Evaluation report, September 2026
Case study
Health Insurance Claims Administration Platform
In continuous production since 2020 for an insurer's health insurance administration arm, with ongoing maintenance and support since launch.
Case study
Livestock Insurance Management System
After rebuilding it, we continue to run and extend it, including a self-hosted release channel that updates the field app on devices without an app store.
Case study
one2one AI Support Agent Platform
We onboard and operate each client's agents, and re-test them on real conversations before changing models.
Why Biznovelty
We've done it for years.
One of our platforms has been in continuous production since 2020, with about 40 releases.
Disciplined releases.
Changes go through staging before production, with tagged releases and a maintenance window when needed.
AI agents included.
We monitor and re-test AI agents, not just servers and code, because we run our own agent platform.
One accountable team.
A named technical lead who knows your system, instead of whoever is free that day.
Engagement & pricing
Monthly agreement
A level of support matched to your system, with the term and notice period written into your agreement.
Change-request hours
Included hours each month. Extra work is estimated and approved before it starts, at the rate in your agreement.
Systems built by others
Start with a paid Code & Architecture Audit, so we both know what we're taking on.
Pricing
Quoted after the onboarding check, based on your system and the support it needs.
Frequently asked questions
Yes. We start with a Code & Architecture Audit so we both know the system's condition, risks, and what it will take to look after it. Then we agree the right tier.
Tell us what you need looked after
In a 30-minute call we'll learn about your system, suggest a tier, and explain how onboarding would work.