Deploy AI across your business in 90 days

We design, build, and deploy AI solutions, workflows, and automations across your business, fully integrated into your existing systems and processes.

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The ROI Gap

Using AI, But Not Seeing Measurable Impact?

Most companies are already experimenting with AI. But the impact often stays trapped in individual tools, isolated use cases, and ad hoc habits.Without a clear implementation plan, AI rarely turns into measurable efficiency, better decision-making, or business ROI.

Manual Workflows

Core processes still rely on repetitive, manual effort.

Fragmented Data

Information is spread across systems with no clear connection.

Slow Reporting

Insights take too long and lack consistency across the business.

Scattered AI Use

Tools are used in isolation without clear ROI or direction.
In 90 Days

What You Will Have by the End of the Program

Clear AI Roadmap

A prioritised plan aligned with your operations and business goals.

Live AI Workflows

3–5 deployed solutions across your highest-impact processes.

Connected Systems

Data flows seamlessly between tools to enable real automation.

Less Manual Work

Reduce repetitive tasks across your core operations.

AI-Enabled Teams

Your team actively uses AI in their day-to-day work.

Measurable Results

Faster workflows, improved efficiency, and stronger output.
HOW IT WORKS

How the 90 Day AI Enablement Program Works

A structured implementation program designed to move your business from AI experimentation to operational deployment.

1
Weeks 1-2

Discovery & Design

We start by understanding how your business actually operates today and where AI can create the most value.

Analyse key workflows and operational processes

Define approval structures and decision points

Establish knowledge bases and data sources

Align on success metrics and business outcomes

Outcome
A clear, prioritised roadmap of AI solutions tailored to your business.
2
Weeks 3–5

Build

We begin building and connecting the core AI solutions and workflows.

Develop 3–5 high-impact AI solutions

Integrate with your systems (CRM, finance, internal tools)

Define workflow logic, routing, and automation rules

Test using real or representative business scenarios

Outcome
Working solutions connected to your systems and ready for live testing.
3
Weeks 6–9

Pilot

We deploy solutions into controlled environments and refine based on real usage.

Run live use cases with your team in the loop

Measure cycle times, output quality, and efficiency gains

Refine prompts, workflows, and logic

Strengthen tracking, logging, and auditability

Outcome
Validated solutions that perform reliably in real business conditions.
4
Weeks 10–12

Production

We transition from pilot to full deployment across your business.

Production-level deployment and system hardening

Enablement of teams with clear workflows and usage

Documentation and SOPs for ongoing use

Define next-phase opportunities and roadmap

Outcome
Fully operational AI-enabled workflows embedded into your business.
5
Ongoing

Maintenance

We continue to support, optimise, and evolve your AI solutions as your business grows.

Analyse key workflows and operational processes

Define approval structures and decision points

Establish knowledge bases and data sources

Align on success metrics and business outcomes

Outcome
A clear, prioritised roadmap of AI solutions tailored to your business.
CUSTOM AI SOLUTIONS

Examples of Custom AI Solutions We Implement

Every business is different, so every implementation is tailored to your systems, workflows, and team. These examples show the types of AI solutions we can design, build, and deploy during the 90-Day AI Enablement Program.

Deal Desk and Proposal Agent
Automates the proposal process from quote request to approved document.
Triggered from Salesforce, the agent pulls opportunity details, CPQ pricing, Xero billing history, and approved templates from SharePoint. It drafts the proposal, checks pricing and terms against approval rules, flags exceptions, and routes only what needs approval to Finance or Legal.
Once approved, it prepares the final proposal for rep review and sends it to DocuSign.
Outputs

Draft proposal

Pricing and exception summary

Approval brief

Updated CRM and document status

Expected Business Impact

Faster quote turnaround

Fewer pricing errors

Less margin leakage

Reduced internal coordination burden

Core Systems
Collections and Dispute Agent
Automates collections follow-up and dispute handling across overdue accounts.
Running daily, the agent pulls invoice and payment data from Xero, account ownership and customer notes from Salesforce, email history from Outlook, and supporting documents from SharePoint. It prioritises accounts by balance, age, and behaviour, drafts reminder emails, classifies customer replies, assembles dispute packs, and routes follow-up to the right owner.
Outputs

Prioritised collections worklist

Draft reminders

Dispute evidence pack

Promise-to-pay tracker

Escalation tasks

Expected Business Impact

Lower collector admin time

Faster dispute resolution

Improved collections focus

Reduced DSO pressure

Core Systems
Order Exception Resolution Agent
Automates order hold triage and resolution across stock, pricing, credit, SKU, and delivery issues.
Triggered by hold status, PO inbox activity, or failed EDI validation, the agent reads the order, inventory data, customer pricing, CRM notes, and approved substitution rules. It recommends the next best action, drafts the customer response, routes ownership, and tracks the order until the hold is resolved.
Outputs

Structured exception queue

Recommended resolution path

Draft customer communications

Owner assignment

Order status updates

Expected Business Impact

Faster order release

Less manual triage

Clearer ownership

Better customer communication

Core Systems
Support Escalation Briefing Agent
Automates escalation preparation so engineering receives complete, structured context from the start.
Triggered by severity level, SLA breach, or manual escalation, the agent pulls the Zendesk thread, Salesforce account context, Datadog logs, prior incidents, and relevant knowledge articles. It assembles an escalation brief with customer impact, timeline, attempted fixes, likely issue category, and missing information. It also opens or updates the Jira issue and drafts a customer update for support review.
Outputs

Structured escalation brief

Next-step diagnostic suggestions

Draft customer update

Linked records across support and engineering

Expected Business Impact

Better engineering handoffs

Faster escalation prep

Fewer repeated questions

Quicker resolution on critical cases

Core Systems
Month-End Commentary Agent
Automates finance commentary drafting so FP&A can spend more time analysing what needs action.
Triggered when close is complete, the agent pulls actuals from Xero, budget and forecast files from SharePoint, and commercial context from Salesforce. It compares results against prior periods, forecasts, and thresholds, then drafts branch-level and consolidated commentary. It also flags anomalies, identifies gaps, and sends targeted follow-up questions to managers in Teams.
Outputs

Branch commentary

Executive summary commentary

Anomaly and variance flags

Targeted follow-up prompts

Expected Business Impact

Faster reporting cycle

More consistent commentary

Reduced manual drafting

Better management attention on material issues

Core Systems
Campaign QA Agent
Automates pre-launch campaign checks across content, audience logic, routing, compliance, and webinar setup.
Triggered when a campaign is marked “Ready for Review” or enters its launch window, the agent reviews campaign assets, forms, workflows, audience rules, webinar settings, Salesforce routing, and approved disclaimer libraries. It checks consistency against the campaign brief, flags issues, suggests fixes, and sends a launch-readiness report to marketing and compliance.
Outputs

Launch-readiness report

Ranked issue list

Recommended fixes

QA and approval record

Expected Business Impact

Lower QA effort

Fewer post-launch corrections

Reduced compliance risk

Better campaign readiness

Core Systems
Contract Review Prep Agent
Automates contract intake and first-pass review preparation so Legal can focus on actual risk and negotiation.
Triggered when a contract is uploaded to the CLM workspace or a deal moves to “Legal Review,” the agent identifies the document type, extracts key clauses and metadata, pulls commercial context from Salesforce, retrieves fallback language from SharePoint, and checks prior negotiated positions. It then prepares a deviation matrix and issue summary for counsel.
Outputs

First-pass review pack

Clause deviation summary

Fallback language suggestions

Structured contract metadata

Expected Business Impact

Faster first-pass review

More consistent playbook use

Less senior legal time spent on prep work

Core Systems
Deal Memory & Investment Brief Agent
Automates deal knowledge capture and brief creation so teams can move faster with better continuity.
Triggered when a deal workspace is created, new documents are added, or a fresh brief is requested, the agent reads investment notes, emails, diligence files, meeting summaries, prior memos, and decision logs. It builds a current deal view, summarises thesis and risks, tracks open diligence items, and produces a structured investment brief with citations back to source materials.
Outputs

Current deal brief

Thesis and risk summary

Open diligence tracker

Handoff note with source references

Expected Business Impact

Less time spent reconstructing context

Stronger continuity across the team

Faster brief preparation

Lower risk of key information being lost

Core Systems
Deal Desk and Proposal Agent
Business Problem
Sales teams often lose time and margin because proposal creation depends on manual coordination across Sales, Finance, Legal, and Sales Operations. Quotes move slowly, pricing exceptions are handled inconsistently, and reps become the bottleneck between functions.
Current Workflow
When a deal reaches proposal stage, the account executive pulls opportunity details from Salesforce, checks pricing and configuration in CPQ, reviews prior customer terms, edits an old proposal, and manually chases approvals. Finance and legal often receive incomplete context, ask follow-up questions, and create avoidable delays. CRM status is frequently outdated by the time the proposal is ready.
Agent Workflow
The agent is triggered when an opportunity moves to “Quote Requested” in Salesforce. It validates the opportunity record, pulls pricing and quote-line data from CPQ, checks customer billing history in Xero, retrieves the correct proposal template and approved clause library from SharePoint, and drafts the proposal. It compares pricing and terms against approval thresholds, prepares an exception summary, and routes only genuine exceptions to finance or legal. Once approvals are complete, it packages the final draft for rep review and sends the approved version to DocuSign.
Core Systems
Outputs

Draft proposal

Pricing and exception summary

Approval brief

Updated CRM and document status

Human Oversight
Sales managers approve discount exceptions. Legal approves non-standard terms. Sales remains final reviewer before anything is sent externally.
Expected Business Impact

Faster quote turnaround

Fewer pricing errors

Less margin leakage

Reduced internal coordination burden

Collections and Dispute Agent
Business Problem
AR teams spend too much time chasing overdue invoices, gathering missing backup, and manually forwarding disputes. High-value accounts can get buried in low-priority follow-up, slowing collections and extending DSO
Current Workflow
Collectors export aging reports from Xero, review overdue invoices one by one, check whether the customer has invoice copies or proof of delivery, and manually coordinate with sales or finance when disputes arise. Promise-to-pay dates are often tracked inconsistently, and internal escalation is fragmented.
Agent Workflow
The agent runs daily against overdue invoices and again when customers reply to collection emails. It pulls invoice and payment data from Xero, account ownership and customer notes from Salesforce, email history from Outlook, and supporting documents from SharePoint. It prioritises accounts by balance, aging, and behavior, drafts reminder emails, classifies inbound replies, assembles dispute packs, and routes follow-up to the correct owner.
Core Systems
Outputs

Prioritised collections worklist

Draft customer reminders

Dispute evidence pack

Promise-to-pay tracker

Routed escalation tasks

Human Oversight
AR owns escalations, concessions, and payment plan decisions.
Expected Business Impact

Lower collector admin time

Faster dispute resolution

Improved collections focus

Reduced DSO pressure

Order Exception Resolution Agent
Business Problem
Order holds caused by stock issues, pricing mismatches, credit blocks, obsolete SKUs, and delivery constraints slow revenue recognition and overload customer service teams.
Current Workflow
Customer service enters orders, identifies issues, then manually checks inventory, pricing, account context, and substitution options while emailing customers, sales, and operations. Simple and complex exceptions end up mixed together, and order aging increases.
Agent Workflow
The agent is triggered when an order enters hold status, when a PO email lands in the inbox, or when an EDI transaction fails validation. It reads the sales order, product and inventory data, customer pricing, CRM notes, and approved substitution rules. It recommends the next best action, drafts the customer response, routes the task to the correct owner, and tracks the order until the hold is resolved.
Core Systems
Outputs

Structured exception queue

Recommended resolution path

Draft customer communications

Owner assignment

Order status updates

Human Oversight
Customer service approves substitutions, pricing overrides, split shipments, and credit-sensitive releases.
Expected Business Impact

Faster order release

Less manual triage

Clearer ownership

Better customer communication

Support Escalation Briefing Agent
Business Problem
Engineering escalations are often poorly prepared, which leads to slower resolution, more customer back-and-forth, and wasted effort across support and engineering.
Current Workflow
When a ticket becomes urgent, frontline support has to gather history from Zendesk, account context from Salesforce, logs from Datadog, prior incidents, internal conversations, and release notes. Engineering often receives incomplete escalations with missing reproduction steps and limited business context.
Agent Workflow
The agent is triggered when a ticket reaches a severity threshold, breaches SLA, or is escalated. It pulls the Zendesk thread, Salesforce account context, relevant logs, prior incidents, and knowledge articles, then assembles a structured escalation brief. It includes customer impact, timeline, attempted fixes, likely issue category, and missing information. It also opens or updates the Jira issue and drafts a customer update for support review.
Core Systems
Outputs

Structured escalation brief

Next-step diagnostic suggestions

Draft customer update

Linked records across support and engineering

Human Oversight
Support leadership approves critical escalations and all high-severity external messaging.
Expected Business Impact

Better engineering handoffs

Faster escalation prep

Fewer repeated questions

Quicker resolution on critical cases

Month-End Commentary Agent
Business Problem
FP&A teams spend too much time turning numbers into commentary and too little time analysing what actually needs action.
Current Workflow
After close, analysts export actuals, compare against budget and forecast, chase managers for explanations, rewrite responses into a consistent narrative, and manually assemble the final management pack.
Agent Workflow
The agent is triggered when close is marked complete. It pulls actuals from Xero, combines them with budget and forecast workbooks from SharePoint, adds relevant commercial context from Salesforce, and compares results against prior periods and thresholds. It drafts branch-level and consolidated commentary, identifies gaps or contradictions, and sends targeted follow-up questions to managers in Teams. Responses are then folded back into the draft for finance review.
Core Systems
Outputs

Branch commentary

Executive summary commentary

Anomaly and variance flags

Targeted follow-up prompts

Human Oversight
FP&A or the CFO approves all final narrative before circulation.
Expected Business Impact

Faster reporting cycle

More consistent commentary

Reduced manual drafting

Better management attention on material issues

Campaign QA Agent
Business Problem
Campaign launches are delayed or exposed to risk because checks across copy, audience logic, routing, disclaimers, and webinar setup are fragmented across teams.
Current Workflow
Marketing manually checks campaign assets, compliance reviews content without full context, and sales operations separately checks routing. Despite several reviewers, issues like broken links, missing disclaimers, incorrect audience targeting, or faulty lead routing still slip through.
Agent Workflow
The agent is triggered when a campaign is marked “Ready for Review” or enters its launch window. It reads campaign assets, forms, workflows, audience logic, webinar settings, Salesforce routing rules, and approved disclaimer libraries. It runs a preflight check, verifies consistency against the campaign brief, flags issues, proposes corrections where possible, and sends a launch-readiness report to marketing and compliance.
Core Systems
Outputs

Launch-readiness report

Ranked issue list

Recommended fixes

QA and approval record

Human Oversight
Marketing operations and compliance approve audience logic, claims, disclosures, and final launch.
Expected Business Impact

Lower QA effort

Fewer post-launch corrections

Reduced compliance risk

Better campaign readiness

Contract Review Prep Agent
Business Problem
Legal teams lose time doing operational detective work before they can do actual legal review.
Current Workflow
Sales sends agreements to legal with limited commercial context. Legal then has to identify document type, compare customer language to the playbook, reconstruct deal history, and check prior negotiated positions before beginning review.
Agent Workflow
The agent is triggered when a contract is uploaded to the CLM workspace or when a deal moves to “Legal Review.” It identifies document type, extracts key clauses and metadata, pulls commercial context from Salesforce, retrieves fallback language from SharePoint, checks prior negotiated positions, and prepares a first-pass deviation matrix with an issue summary for counsel.
Core Systems
Outputs

First-pass review pack

Clause deviation summary

Fallback language suggestions

Structured contract metadata

Human Oversight
Counsel approves all outbound redlines and any change in fallback position or risk posture.
Expected Business Impact

Faster first-pass review

More consistent playbook use

Less senior legal time spent on prep work

Deal Memory & Investment Brief Agent
Business Problem
Important deal context often sits across inboxes, notes, diligence files, and individual memory, making handoffs slow and decision-making inconsistent.
Current Workflow
To get up to speed on a deal, someone has to search across folders, emails, notes, and prior memos to reconstruct the thesis, current status, open issues, and recent developments. Continuity depends too heavily on who remembers what.
Agent Workflow
The agent is triggered when a new deal workspace is created, when new documents are added, or when a fresh brief is requested. It reads investment notes, emails, diligence files, meeting summaries, prior memos, and decision logs. It assembles a current deal view, summarises thesis and risks, tracks open diligence items, and produces a structured investment brief with citations back to source materials.
Core Systems
Outputs

Current deal brief

Thesis and risk summary

Open diligence tracker

Handoff note with source references

Human Oversight
The investment team validates the thesis, risk framing, and any decision-useful output before circulation.
Expected Business Impact

Less time spent reconstructing context

Stronger continuity across the team

Faster brief preparation

Lower risk of key information being lost

Built Around Your Existing Tools and Infrastructure

We integrate AI into the systems your team already uses, so the solution fits into your business instead of forcing your business to change around the solution.

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Zendesk logo
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Why our program is successful

Most AI initiatives fail to deliver meaningful impact because they stay at the level of tools, experiments, or isolated use cases. This approach is different. It is designed to move from fragmented usage to operational implementation.

Workflow-First, Not Tool-First

We start with how your business operates, not tools. By focusing on real workflows, we apply AI where it reduces friction and improves outcomes.

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Built Around Your Existing Systems

AI only works when connected. We integrate with your CRM, finance tools, and systems so solutions fit naturally into your workflows.

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Structured, Time-Bound Delivery

Open-ended AI projects fail. This is a focused 90-day program with clear scope, milestones, and measurable outcomes that drive real progress.

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Human-in-the-Loop by Design

Not everything should be automated. We design solutions with approvals and checkpoints so your team stays in control while reducing repetitive work.

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Built for Adoption, Not Just Deployment

AI projects fail due to poor adoption, not tech. We build workflows your team actually uses and embed them into daily operations.

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From Use Cases to Operating Model

We don’t build isolated tools. We create a foundation for ongoing AI adoption with a repeatable approach to building and scaling solutions.

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Designed for Businesses Ready to Operationalise AI

This program is best suited for companies that:

Have 50 to 500+ employees

Operate across multiple systems, teams, and workflows

Are already experimenting with AI but lack structure

Want to move from isolated use cases to implemented solutions

Have clear operational bottlenecks worth solving

Can assign an internal owner to support implementation

Next steps

1.

Book a strategy call

We’ll understand your business, systems, and current AI maturity.

2.

Align on opportunities

We’ll discuss where AI could create the biggest operational impact.

3.

Receive a tailored proposal

You’ll receive a clear plan for scope, timeline, and solutions.

4.

Begin implementation

Once aligned, we begin the 90-day enablement program.

Ready to move from AI experimentation to AI implementation?

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