The problem

Every inbound enquiry looks the same in an inbox until someone reads it. Teams spend time triaging low-intent messages before they ever reach a real opportunity, and high-intent leads can sit unanswered behind them.

The solution

An AI model reads each enquiry, evaluates buying intent against context you define, and assigns a qualification label and score before a human ever opens it.

How it works

1. 1.An enquiry is submitted through a form or API.
2. 2.The message is sent to an AI model with instructions on what a qualified lead looks like for your business.
3. 3.The model returns a structured qualification — a label, a score, and a reason.
4. 4.The qualified lead is stored and made available to your team, prioritized by score.

Example use cases

• Scoring inbound enquiries from a website contact form
• Prioritizing which leads a sales team calls first
• Filtering low-intent submissions before they reach a CRM

The problem

Most support volume is the same handful of questions — shipping times, return windows, order status — repeated constantly. Answering them by hand is slow for customers and repetitive for teams, but a bot that guesses at policy is worse than no bot at all.

The solution

An AI assistant answers only from a knowledge base you control, returns a structured decision on every reply, and recognizes when a request needs a person instead of guessing.

How it works

1. 1.A customer sends a message through a chat interface.
2. 2.The system retrieves relevant knowledge base entries for that question.
3. 3.An AI model answers using only that knowledge, or flags the request for a human.
4. 4.Resolved answers are returned instantly; flagged requests are escalated and logged.

Example use cases

• Answering shipping, returns, and order-status questions instantly
• Escalating refund exceptions or complaints to a human
• Keeping a full record of every conversation and outcome

The problem

Sales teams lose time on manual handoffs — copying a lead into a CRM, assigning an owner, scheduling a follow-up. Each manual step is a place a lead can stall or get missed entirely.

The solution

Once a lead is captured or qualified, automation handles routing, CRM updates, and follow-up scheduling without someone doing it by hand.

How it works

1. 1.A lead or event triggers the workflow (new enquiry, status change, qualification result).
2. 2.Business rules determine routing — by territory, product, or lead score.
3. 3.The CRM record is created or updated automatically.
4. 4.Follow-up tasks or reminders are scheduled for the right owner.

Example use cases

• Routing qualified leads to the right salesperson automatically
• Keeping CRM records in sync with form submissions and other tools
• Scheduling follow-up reminders without manual data entry

The problem

Businesses run on a patchwork of tools — spreadsheets, email, a CRM, a database — that don't talk to each other. Someone ends up manually copying information between them, which is slow and error-prone.

The solution

An automation layer connects the tools you already use, moving and transforming data between them on a trigger, without manual re-entry.

How it works

1. 1.Identify the repetitive process and the systems involved.
2. 2.Define the trigger — a new record, a form submission, a schedule.
3. 3.Build the automation that connects the systems via their APIs.
4. 4.Monitor and adjust as your processes change.

Example use cases

• Syncing data between a form, a database, and a spreadsheet
• Automating repetitive multi-step approval or notification processes
• Eliminating manual data entry between disconnected tools