Real Problems, Real Solutions: AI Use Cases

Challenge:

A mid-sized service firm was spending 15+ hours weekly manually scheduling and rescheduling applicant interviews. The process involved multiple back-and-forth emails between applicants, hiring managers, and coordinators, leading to delays, confusion, and missed opportunities.

Solution:

We implemented an automated scheduling system integrated with their CRM that:

• Automatically sent available time slots based on hiring manager calendars
• Allowed applicants to self-schedule through a personalized link
• Sent automated reminders and rescheduling options
• Updated interview status in the CRM in real-time

Challenge:

A law firm specializing in corporate law was spending 20+ hours per week manually reviewing, categorizing, and extracting key information from contracts and legal documents. This process was not only time-consuming but also prone to human error.

Solution:

We built a custom document automation system that:

• Automatically categorized incoming documents by type
• Extracted key information (dates, parties, terms, etc.) using OCR and NLP
• Generated summary reports highlighting critical clauses and conditions
• Flagged potential issues or discrepancies for attorney review
• Integrated with their document management system

Challenge:

Many service-based businesses struggle with inefficient lead generation or outreach. Agents spend significant time weekly on calls with low contact rates and inconsistent tracking. Manual data entry into CRM systems is error-prone and time-consuming.

Solution:

We developed an AI-powered calling automation system that:

• Deployed conversational AI for initial screening calls
• Intelligently categorized call outcomes
• Used GPT-4 to analyze transcripts and generate accurate summaries
• Automatically updated the CRM/database with results and sentiment
• Sent instant email alerts to agents for hot leads
• Tracked call metrics and sentiment over time

Challenge:

A wealth management firm needed a reliable way to monitor trailing stop losses across diverse asset categories (Stocks, Funds/ETFs). Manual tracking was time-intensive, prone to delays, and risked missing critical price triggers, hindering timely portfolio adjustments.

Solution:

We built a custom Flask web dashboard featuring:

• Tabbed interface for asset categorization (e.g., Stocks, Funds/ETF).
• Excel (.xlsx, .xls) ticker uploads per category.
• Live price fetching via `yfinance` on upload/reset.
• Automatic calculation of 8% and 16% stop levels based on initial price.
• Clear status display (OK, 8% Triggered, 16% Triggered) with visual highlighting.
• Independent sorting, filtering, and searching within each category tab.
• Options to reset initial price or delete individual tickers within their category.
• Global export functionality for triggered assets (8% or 16%) across all categories.
• Persistent data storage (JSON) and automated background price updates (every 5 mins) via Render Cron Jobs.
• Client branding and dark mode toggle.

Challenge:

Businesses across industries face significant revenue loss due to slow lead response times. Manual lead distribution is often inconsistent, leading to delays, missed opportunities, and decreased conversion rates as potential customers lose interest or engage with competitors.

Solution:

We implemented a high-speed lead management automation that:

• Monitors multiple lead sources (web forms, registrations, job boards, etc.) in real-time.
• Instantly routes and assigns new leads to the appropriate team member based on defined logic (e.g., round-robin, territory, specialty).
• Automatically updates the lead status and ownership in the company's central system/database.
• Creates an immediate follow-up task for the assigned agent with a priority flag.
• Triggers instant notifications (e.g., email, Slack) to the assigned agent.
• Sends an automated, personalized welcome text message (SMS) to the lead upon assignment.
• Logs all assignment actions and timestamps for tracking and reporting.

Challenge:

Many organizations struggle with inconsistent or incomplete job data entered manually or imported from various sources. Variations in titles, missing shift details, inconsistent formatting, and lack of proper categorization make it difficult to search, match candidates effectively, and present opportunities professionally on public platforms. Manual standardization is extremely time-consuming and prone to errors.

Solution:

We implemented an intelligent automation workflow that leverages AI to:

• Automatically retrieve job orders requiring processing from the source system.
• Analyze job titles and descriptions to generate clean, standardized titles (e.g., removing extraneous information).
• Parse descriptions and custom fields to extract and structure key details like work schedules, hours per week, and employment patterns (e.g., "Full-time", "Contract", "Part-time").
• Intelligently determine and assign the correct functional classifications based on content analysis against predefined organizational taxonomies.
• Generate a well-formatted HTML job summary, ensuring essential information (like assignment length, required skills, contact info) is included consistently.
• Update the job record in the source system with the standardized title, extracted details, functional classifications, and the generated HTML summary.

Challenge:

Professionals often face overflowing Outlook inboxes filled with a mix of critical client messages, new inquiries, newsletters, SaaS updates, receipts, and junk mail. Manually sorting this volume daily consumes significant time, increases the risk of missing important communications, and reduces overall productivity.

Solution:

We developed an intelligent n8n automation integrated with OpenAI and Microsoft Outlook that:

• Monitors the Outlook inbox for new emails in real-time.
• Extracts key data: subject, sender, and body content.
• Utilizes an AI model (GPT-4o) trained with specific instructions to analyze the email's context and purpose.
• Dynamically fetches available Outlook folder IDs.
• Determines the most appropriate category based on predefined rules (Actionable, Junk, Receipt, SaaS, Community, Business, Other).
• Prioritizes keeping the main Inbox clear for actionable items only.
• Automatically moves non-actionable emails to their corresponding categorized folders within Outlook.

Challenge:

Professionals in credential-heavy fields often struggle to maintain, format, and tailor complex profiles or resumes efficiently. Manual updates are time-consuming, inconsistent, and don't leverage modern AI for optimization.

Solution:

We developed a modern web application enabling professionals to build and manage their profiles effectively:

• Seamless parsing of existing Resume/CV documents using AI.
• Generation of professional PDF documents from profile data using various templates.
• Intuitive interface to edit, enhance, and organize profile content (experience, credentials, etc.).
• AI-powered generation of concise and impactful profile summaries.
• Secure storage and management of professional profiles.

Challenge:

Non-profits, parishes, and local churches often lack dedicated financial expertise and struggle to interpret complex spreadsheet data. Manual analysis is laborious, limiting their ability to understand financial health, identify trends, and plan effectively.

Solution:

We created a specialized financial analysis application designed for non-profits:

• Automatic processing and ingestion of standard Excel financial statements.
• Clear, interactive visualizations of revenue sources and expense breakdowns.
• Automated comparison of actual financial results against budgets.
• Identification and highlighting of significant financial trends over time.
• AI-powered forecasting to project future financial positions based on historical data.
• Integrated AI financial assistant allowing users to ask plain language questions about their data (e.g., "What was our biggest expense last quarter?").
• Secure data handling tailored to organizational needs.

Challenge:

Manual cold outreach is inefficient and costly. Teams waste hours cross-referencing leads, cleaning lists, and manually tracking interactions, leading to duplicate contacts, inconsistent follow-up, missed opportunities, and ultimately, lost revenue potential.

Solution:

We deployed a sophisticated, platform-agnostic automation engine that leverages AI to transform cold email outreach:

• Intelligent Lead Verification: Instantly cross-references new prospects against existing systems (CRM, databases) to prevent duplicate outreach and protect existing relationships.
• AI-Powered Personalization Engine: Utilizes advanced web scraping (LinkedIn profiles, company sites, deep web research via Jina AI) to gather prospect intelligence. This data feeds into a GPT-4 AI model which generates hyper-personalized email introductions and subject lines tailored to the individual's role, company, and recent activity.
• Automated Deduplication & List Hygiene: Ensures clean, accurate contact lists, boosting deliverability and brand reputation.
• Personalized Email Sequencing: Delivers the AI-crafted messages at scale via platforms like Instantly.ai, triggered by prospect segments or specific engagement actions (or lack thereof).
• Real-time Engagement Monitoring & CRM Integration: Automatically tracks campaign status and responses, updating lead records and metrics in systems like Pipedrive for seamless pipeline management.
• Unified Campaign Analytics: Consolidates performance metrics, providing clear visibility into campaign effectiveness and lead progression.