L1 service desk
First response, triage and resolution of common requests, with clear routing for everything else.
Application & Data Platform Support
Support for the applications and data your business runs on.
We provide L1 to L3 support for your business applications, data pipelines and ML models in production. Tickets are handled against clear SLAs, recurring problems are fixed at the root and you see it all in a monthly service review.
The problem
Why support gets in the way.
01
Engineers stuck on support
Your product engineers spend their days answering tickets and fixing data issues instead of building.
02
Data problems found by the business
A pipeline fails overnight and the first sign is a wrong number in a morning report.
03
Models nobody watches
ML models go live and are never checked again, while their data and accuracy slowly drift.
04
No clear ownership
Tickets bounce between teams and vendors, and nobody can say how long issues take to resolve.
What we deliver
Support across apps, data and models.
One team, one process and one set of SLAs, from the first ticket to the code fix.
L2 application support
Investigation of issues in configuration, data and integrations, with fixes that do not need code changes.
L3 engineering fixes
Code-level fixes by engineers who know your applications, released through your normal process.
Data pipeline support
Monitoring of pipelines and warehouses for failures, freshness and quality, with issues fixed before reports go out.
ML model support
Monitoring of models in production for drift, accuracy and cost, with retraining and rollback when needed.
Problem management
Recurring issues traced to their cause and fixed, so ticket volume falls over time.
How we deliver
From handover to steady support.
We learn your systems first, then take on support level by level.
Always included
- A named service manager and a clear escalation matrix
- A monthly service review with SLA reporting
- Runbooks and documentation that you own
- Access through your SSO with audit trails, and an NDA and DPA as standard
Typical tools
01
Weeks 1 to 2
Assess
We review your applications, data platforms and current support.
- Applications, pipelines and models in scope agreed
- Ticket history and recurring issues reviewed
- Baseline for ticket volume and resolution times
02
Weeks 2 to 6
Transition
We take over support with no gap in coverage.
- Runbooks and knowledge base written in your tools
- Shadowing, then reverse shadowing on live tickets
- SLAs, escalation matrix and channels agreed
03
Months 2 to 3
Stabilise
Backlogs are cleared and the most common issues are fixed.
- Ticket backlog worked down
- Monitoring added for pipelines and models
- Top recurring issues fixed at the root
04
Ongoing
Optimise
Support becomes quieter and more predictable.
- Monthly service review with SLA reporting
- Self-service answers for common requests
- Fixes and automation planned for repeat issues
Where we apply it
Industries we know well.
FAQ
Questions we hear a lot.
What do L1, L2 and L3 mean in practice?
L1 handles first response, triage and common requests. L2 investigates issues in configuration, data and integrations and fixes what does not need code. L3 is engineers making code-level fixes and finding root causes. We can cover all three or only the levels you need.
Can you support applications built by someone else?
Yes. Many of the systems we support were built by in-house teams or other vendors. We spend the first weeks learning them and writing runbooks before we take over.
What SLAs do you work to?
Our standard targets are P1 15 minutes to respond and 4 hours to resolve, P2 30 minutes and 8 hours, P3 4 hours and 3 days, and P4 1 day and the next release. Final targets are agreed in your contract and reported every month.
Fully managed, co-managed or on-demand pods: which should we choose?
Fully managed means we own support for the agreed systems against SLAs. Co-managed means we take some levels or hours, such as L1 and L2 or out-of-hours cover, while your team keeps the rest. On-demand pods suit a specific job, such as clearing a backlog or stabilising a data platform, billed per sprint.
Do you support data pipelines and ML models as well as applications?
Yes. We monitor pipelines, warehouses and models in production, including data freshness, quality, drift and model performance, and fix issues before they reach reports or customers.
Other managed services
Run the rest with us too.
Cloud Management & FinOps
Day-to-day running of AWS, Azure and GCP, with cost kept under steady watch.
Infrastructure & Platform Engineering
Infrastructure as code, Kubernetes platforms and golden paths for product teams.
DevOps & CI/CD
Pipelines that build, test, scan and deploy on every merge, with fast rollbacks.
Release Management
Release calendars, change approvals, feature flags and canary rollouts.
QA & Test Automation
Test strategy, automated regression, performance and API testing.
SRE, Monitoring & 24x7 Support
Observability, on-call and incident response around the clock.
Digital Transformation & Modernisation
Cloud migration, monoliths to services and manual processes to digital workflows.
Our services
AI strategy, GenAI and agents, data platforms, analytics, MLOps and transformation.
Talk to a founder about Application.
Tell us where you are. We will come back within one business day with a point of view, not a sales deck.