Services
Four areas where AI agents reliably save time today, building your own AI team — and a structured way to start.
Customer support automation
The problem
Most support teams spend their day on the same few dozen questions. Response times grow with volume, quality depends on who is on shift, and scaling means hiring.
What we build
- Intake from email, chat and other channels into one queue
- Automatic categorisation of requests
- Answer drafts based on your knowledge base, policies and order or customer data
- Brand tone of voice settings
- Review interface: approve, edit or escalate
- Optional actions with approval — returns, address changes, status updates
Typical result
Operators review and send drafts instead of writing every answer. We check upfront which steps happen outside the helpdesk — in ERP or other systems — because they often set the real limit.
Business monitoring & analytics
The problem
Someone opens five to ten dashboards every morning to check that nothing broke overnight. Problems that start at night or on weekends are found hours later — after they have cost money.
What we build
- Connections to payments, accounting, CRM, inventory, infrastructure and other systems with an API
- Baselines learned from historical data, plus explicit thresholds
- Anomaly detection with context: what changed, how far from normal, since when
- Alerts to Slack, Telegram, email or SMS by severity
- Daily and weekly trend reports
- Optional automatic actions within limits you define
Typical result
Problems are flagged when they start, not at the next manual check; no routine dashboard reviews.
Hiring & HR automation
The problem
Hiring managers either rely on short subjective summaries of screening calls or spend hours watching recordings. Candidates are compared inconsistently.
What we build
- Competency matrix for the role, built with your team
- Transcription and analysis of interview recordings
- Competency-by-competency assessment with flagged gaps
- Comparable scoring across candidates
- Feedback for recruiters on what they didn't cover
Typical result
A structured report per interview instead of watching the full recording.
Internal operations & integrations
The problem
Data moves between CRM, accounting, spreadsheets and messengers by hand. Reports are assembled manually and arrive late.
What we build
- Document intake and data extraction (invoices, forms, contracts)
- Automated management reporting from multiple sources
- Data pipelines and integrations between your systems
- Internal assistants over your documentation
Typical result
Reports and data transfers that used to take hours run on schedule without manual work.
AI team build-out
The problem
Companies that want their own AI capability rarely know how to hire for it: which skills matter, what the market pays, how to tell a strong engineer from a confident one.
What we build
- Competency matrix and market salary ranges for AI roles
- Technical interviews and selection, together with your HR team
- Onboarding and upskilling in AI development practices
- Management of the team during the first months
- Hand-over to your IT department with processes the team keeps
Typical result
An in-house AI team that keeps working after we step out.
Engagement model
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Process audit
Fixed fee. A map of the process, current workload, automation options with estimated impact and a go / no-go recommendation. Credited against implementation if you proceed.
$300
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Implementation
Fixed scope or time and materials, agreed after the audit. Typical timeline: 3–8 weeks depending on integrations.
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Support
Monthly fee covering monitoring, model and prompt updates, infrastructure and API usage.
Have a process that eats your team's time?
Tell us what it is. We'll come back with an initial assessment of what can be automated and what it would take.