Operate

AI Managed Services: we run what we build, monitored, tuned, on call.

Shipping an agent is the start; keeping it reliable as your business changes is the work. Our managed service operates your autonomous systems day and night. Watching the audit trail, tuning agents as workflows shift, and staying on call. So the value compounds instead of decaying after go-live.

24/7 autonomous operations, humans on call

99.9% platform uptime under autonomous load

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Outcomes

What you get, stated as results.

Autonomous systems kept reliable long after go-live
Defined SLAs and incident response for agent operations
A partner that extends autonomy as each workflow proves out

Capabilities

What this practice covers.

24/7 operations

Round-the-clock monitoring of agent health, throughput, and confidence, with humans on call.

Continuous tuning

Agents adjusted as your processes, data, and volumes change, so accuracy holds over time.

Incident response

Defined runbooks and SLAs for when an agent or its infrastructure needs a person, fast.

Audit-trail review

Regular review of the action log to catch drift before it becomes a problem.

Capacity & cost management

Scaling and FinOps handled as an ongoing service, tied to agreed SLOs.

Roadmap partnership

A standing team that extends autonomy to new workflows as the last ones prove out.

The stack behind this service.

Real tools our team works in day to day, not a generic capability list.

Grafana

Datadog

AWS

How it works

A sequenced path, not a big bang.

24/7

Autonomous operations, humans on call

Transition in

We take operational ownership with runbooks, SLOs, and escalation paths agreed.

Monitor & tune

Continuous watch on health and confidence, with agents tuned as work shifts.

Respond & report

Defined incident response and transparent reporting against SLAs.

Extend the estate

Bring new workflows under autonomy as the roadmap advances.

Proof, Not Promises

Real engagements, the results attached to each one.

Incident response time under 15 minutes, around the clock

Community bank, Pennsylvania

Silent failures detected within 10 minutes, not weeks

London borough council

Evaluation accuracy raised from 71% to 88% before launch

Education software firm, Austin

Release cadence moved to every 2 weeks, consistently

Regional cable operator, Southeast

Where it applies

Telecommunications

Ten industries. One audited standard.

Different regulations, different systems of record — the same discipline every time: agents that run inside guardrails and leave a record you can read.

View all industries →

BFSI

Retail & CPG

Telecom

Technology

Healthcare

Public Sector

PropTech

Education

FinTech

AgriTech

Startups

Managed Services case studies

Challenge, solution, results. What this practice has shipped.

Anonymised at the client's request. Each card states the pain point, what we built, and what changed. Plus the service type and country.

04 studies

Web USA

Round-the-clock run support for a community bank banking portal

Community bank, Pennsylvania

Challenge: The bank's online banking portal had been built by a vendor that later withdrew from the market. Two in-house developers kept it running alongside their day jobs, patches lagged months behind, and a weekend outage had taken 14 hours to resolve because nobody was on call.
Solution: AGS took over the portal under a managed service: 24/7 monitoring and on-call, a monthly patch and dependency cycle, quarterly security review and a small improvement budget. Every change goes through a staging environment and the bank's approval, with a change log the auditors can read.
Results: Incident response time under 15 minutes, around the clock
Zero unplanned outages in the first 12 months
Patch backlog cleared in the first 6 weeks

AI Agents UK

Agent fleet monitoring for a London borough council

London borough council

Challenge: The council had six agents in production handling housing enquiries, bin collection queries and benefit-form checks, built by different suppliers. Nobody monitored them as a group: quality drifted unnoticed, one agent quietly failed for a fortnight, and complaints were the first warning sign.
Solution: We brought the agents under one managed service: a single dashboard for volume, confidence, escalations and cost; weekly sampling of conversations by a reviewer; automated alerts on drift; and a monthly report for the digital board. Fixes and prompt changes follow a documented release process.
Results: Silent failures detected within 10 minutes, not weeks
Escalation-to-human rate stabilised at 12%
Monthly agent spend reduced by 19% through tuning

AI MVPs USA

Taking a pilot support agent into production for an Austin edtech firm

Education software firm, Austin

Challenge: A support agent built in a hackathon was answering real customer questions from a laptop under someone's desk. It worked well enough that the company relied on it, but there was no deployment pipeline, no test set, no monitoring and no one responsible when it broke.
Solution: An eight-week hardening engagement followed by a managed service: we rebuilt the agent on a proper pipeline with an evaluation set of 400 real questions, added rate limits, logging and escalation paths, and now run it with monthly evaluation reports and a defined change process.
Results: Evaluation accuracy raised from 71% to 88% before launch
Handling 1,200 conversations per week in production
Hardened and in service within 8 weeks

Apps USA

Release management for a regional cable operator field app

Regional cable operator, Southeast

Challenge: The technician app used by 400 field staff shipped updates irregularly, often breaking something in the process. Each release needed a week of manual testing, technicians learned to avoid updating, and at one point three versions were in use with different work-order formats.
Solution: AGS took on the app's release management: an automated regression suite, device lab testing on the operator's actual handset models, staged rollouts to 10% of technicians first, and a fixed fortnightly cadence. The operator's product owner still decides what ships; we make sure it ships cleanly.
Results: Release cadence moved to every 2 weeks, consistently
Post-release defects reduced by 70% over 6 months
Version spread reduced from 3 to 1 within 2 releases

FAQ

Managed Services: questions, answered.

What does your managed service actually do?

We run the autonomous systems we build. Monitored, tuned, and on call, 24/7 with humans on call. Shipping an agent is the start; we watch the audit trail, tune agents as workflows shift, and respond to incidents, so the value compounds instead of decaying after go-live.

How do you keep agents accurate as our business changes?

Through continuous tuning. Agents are adjusted as your processes, data, and volumes change, so accuracy holds over time. Regular audit-trail review catches drift before it becomes a problem, and capacity and cost are managed as an ongoing service tied to agreed SLOs.

What happens when an agent or its infrastructure fails?

Defined runbooks and SLAs govern incident response for when an agent or its infrastructure needs a person, fast. We take operational ownership with escalation paths agreed up front, then report transparently against those SLAs so you always know how the systems are performing.

Do you only operate systems you built yourselves?

We operate the autonomous systems we build, taking operational ownership with runbooks, SLOs, and escalation paths agreed during transition. From there we act as a standing team that extends autonomy to new workflows as the last ones prove out. Operating and advancing the estate together.

How is cost and capacity handled after go-live?

Scaling and FinOps are handled as an ongoing service, tied to agreed SLOs rather than left to chance. Capacity and cost management run continuously alongside monitoring and tuning, so throughput holds and spend stays predictable as new workflows come under autonomy.

Put Managed Services to work.

Tell us the workflow. We'll show you the shortest path to a running agent.

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