AI ServicesAI Quick Actions & Augmented
AI Quick Actions & Augmented
Flows
The fastest way to get value from AI isn’t a chatbot or a six-month platform project. It’s finding the moments where people lose time and dropping a focused AI action right there.
Engagement
Product & Workflow Design
Typical Duration
3 – 6 weeks
Targeted AI interventions embedded into the tools and workflows people already use. One click to summarise a document. Auto-categorisation when a ticket lands. Draft generation from a brief. These are product enhancements, not products. And they’re where most organisations see the fastest, most tangible return.
Types of quick actions
Summarisation
One-click summaries tailored to the workflow. Legal docs pull out parties, dates, obligations. Support tickets identify the issue and sentiment. Meeting notes list decisions and action items.
Classification & Routing
Incoming items automatically categorised and routed. Confidence-scored. High-confidence items routed automatically, uncertain cases flagged for human review.
Draft Generation
AI generates a first draft from context: reply to a ticket, report from data, proposal section from a brief. Starting point, not final output.
Data Extraction
Structured data from unstructured sources. Names, dates, amounts from contracts. Line items from invoices. Formatted for the downstream system.
Smart Suggestions
Contextual recommendations as the user works. Product suggestions, field auto-complete, next-action recommendations. Less cognitive load, faster decisions.
Quality Checks
AI reviews work as it’s produced: style guide compliance, data validation, inconsistency flagging, compliance issue detection.
How we build them
Identify Friction — Step 1
Map where the team loses time. Best opportunities are frequent, patterned, and time-disproportionate tasks.
01
Identify Friction — Step 1
Map where the team loses time. Best opportunities are frequent, patterned, and time-disproportionate tasks.
02
Design Intervention — Step 2
Where does it trigger, what context does it receive, what does it output, how does the user interact with the result?
Design Intervention — Step 2
Where does it trigger, what context does it receive, what does it output, how does the user interact with the result?
Build & Tune — Step 3
Prompt engineering, context injection, output formatting, integration with existing tools.
03
Build & Tune — Step 3
Prompt engineering, context injection, output formatting, integration with existing tools.
04
Test & Validate — Step 4
Quality testing with real workflow examples. Benchmark against human performance.
Test & Validate — Step 4
Quality testing with real workflow examples. Benchmark against human performance.
Deploy & Monitor — Step 5
Usage tracking, quality monitoring, feedback collection. Track adoption, quality, and impact.
05
Deploy & Monitor — Step 5
Usage tracking, quality monitoring, feedback collection. Track adoption, quality, and impact.
Deliverables
What you get
- Deployed AI actions integrated into existing tools
- Prompt engineering and configuration documentation
- Quality benchmarks and test results
- Monitoring dashboard
- Tuning guide for ongoing refinement
LLMsPrompt EngineeringAPI IntegrationBrowser ExtensionsSlackNotionClaudeGPT-4
Want AI value in weeks, not months?
Quick actions deliver measurable time savings without a major build. If your team is doing repetitive, pattern-based work that eats hours, we can probably help fast.