CUSTOMER SUPPORT
Quality Assurance
Monitor sentiment and compliance across every support interaction.
Available AI Agents
Explore agents built for quality assurance. Deploy instantly or customise for your workflow.
DriveWatch AI — Google Drive Change Monitor
Kloudless used their unified Events API to detect Drive changes reliably across users, enabling sync workloads to detect thousands of file changes per minute
Recursively scans a root Google Drive folder, detects new/modified files since last run, and outputs a batch of changes
- Scheduled monitoring of a root folder and its nested structure
- Recursive traversal through subfolders automatically
- Filters and outputs only newly created or modified files
SmartRoute AI Orchestrator
Salesforce saved 50,000 hours in one quarter using Einstein in Slack to automate routine tasks
Classifies requests and sends them to the best model to maximize relevance, speed, and cost efficiency.
- Automatically classify user requests into categories
- Route each request to the optimal LLM
- Maintain conversation state across turns
SpecForge PRD & Test Studio
T-Mobile cut test-data request time 50% and reduced a validation cycle 14→3 days using Tricentis Tosca.
Turn structured inputs into a professional PRD plus Gherkin test scenarios, merged and exported as a branded PDF. Built for PMs and QA teams to standardize docs and cut busywork.
- Generates a structured PRD from your brief
- Derives aligned Gherkin test scenarios from the PRD
- Merges PRD + tests into one reviewable document
Support Triage Router
Slack cut ticket response from ~2 days to 24 hours, with 97% tickets submitted via Slack using Halp workflows
Scans a support Slack channel for “ticket” reactions, drafts titles/summaries with AI, prevents duplicates, and creates prioritized Linear issues with links back to Slack
- Detects tagged Slack messages and turns them into tickets
- Auto-writes clear titles & summaries from raw messages
- Maps urgency → Linear priority (low/med/high/urgent)
SupportLoop Auto-Responder
Allstate shifted most of 50k daily claimant communications to AI-written, human-verified emails—clearer, less jargony responses
Routes new emails to an AI knowledge base, replies automatically when confident, and escalates to a human expert when not. Human answers are converted into new Q&A pairs to grow your KB continuously
- Auto-replies from a vetted Q&A base in your voice
- Escalates unclear cases to a named expert with full context
- Converts expert replies into reusable Q&A entries automatically
Telegram NeurochainAI - Bot
Jisc pilot engaged 44 institutions in AI image-generation use-cases across higher education.
Integrates neurochainai api for text and image generation inside telegram, enabling creative media interactions.
- Enables instant generation of marketing copy and visuals (text + image) via telegram prompts
- Delivers generated assets into chat, ready‑to‑use and shareable, reducing designer backlog
- Supports routing of generated assets into content calendars or storage systems automatically
Automated Fine-Tuning of OpenAI Models
Khan Academy reduced teacher prep friction (non-teaching tasks often consume up to 50% of teacher time) by adopting AI teaching assistants.
Automates fine-tuning cycles by ingesting labeled training files from google drive, validating & cleaning data, launching OpenAI fine-tune jobs.
- Speeds up dataset-to-model cycles so educators iterate on models in hours instead of days
- Automates data validation and error reporting to stop failed fine-tunes before they start
- Produces human-readable evaluation reports (accuracy, token usage, sample predictions) for curriculum teams
Qualify New Leads Agent
University students using an adaptive-learning AI tool achieved 62% higher test-scores compared to peers — an example of how similar AI technology (though not this exact agent).
Uses OpenAI’s gpt‑4 to analyse new leads entered into a google sheet and prioritise the best ones for sales outreach.
- Automatically reads new lead entries in a google sheet and assigns a qualification score
- Ranks leads by likelihood to convert and flags top‑priority ones for immediate outreach
- Adds structured notes and next‑step suggestions (e.g., “call within 24 h”, “nurture – email drip”)
WordPress PostWriter AI
“Students at UniDistance Suisse using a GPT-3-driven AI tutor improved grades by up to 15 percentile points compared to a parallel non-AI course.” (Example of similar technology)
This workflow uses AI to write wordpress posts based on a few keywords, simplifying the content creation process.
- Creates full blog posts from just keywords or brief prompts
- Formats output for direct import into wordpress (gutenberg blocks or classic editor)
- Generates seo‑compliant meta descriptions and suggests internal/external links
OpenAI-powered Tweet Generator
Baylor College of Medicine achieved a 9.6% tweet engagement rate (mission-based tweets) vs 5.3% for other tweets (example of comparable technology, not this agent).
Generates ready‑to‑post tweets using OpenAI’s language model: input your topic, tone and audience, output high‑impact social copy for Twitter.
- Generates multiple tweet drafts in minutes from a given topic and target audience
- Applies your institution’s brand voice, tone and guidelines to ensure consistency
- Offers variations (e.g., formal, conversational, student‑friendly) to test messaging
Create dynamic Twitter profile banner
University of Sydney achieved 4× higher Instagram campaign engagement rate after revamping visuals across social channels (example of comparable branding technology, not this agent).
Automates the creation of dynamic twitter profile banners: input your institution’s logo, colours and tagline, and deliver ready‑to‑upload visuals across dimensions.
- Generates multiple twitter banner designs in minutes from your brand assets
- Applies brand colours, logo placement and tagline automatically to each design
- Produces both static png and optional animated gif variants for maximum impact
Analyze Feedback using AWS Comprehend
Similar AI tools helped the University of Thessaly process 700+ student comments in one study, enabling detection of teaching-competency issues across courses.
Performs sentiment analysis on feedback using aws comprehend and sends results to mattermost.
- Automatically ingest student open‑ended comments from surveys or forms
- Run sentiment classification and key‑phrase/theme extraction using aws comprehend
- Automatically classify and tag comments by course, instructor or module for drill‑down
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