Harmonising life through systematic thinking.

The Problem

Your team already pays for tools with AI capabilities they're not using. ClickUp Brain, Notion AI, Microsoft 365 Copilot—these features remain dormant while your people spend hours on tasks these tools could assist with.

Our Approach

1. Audit current subscriptions for dormant AI capabilities
2. Configure features and create team-specific prompts
3. Monitor adoption and refine based on what works

Works Well When

• You already subscribe to platforms with AI features
• Your team performs repetitive administrative tasks
• You have at least one person willing to champion adoption

Not Appropriate When

• You need custom AI capabilities not covered by existing platforms
• Your team strongly resists technology changes

Engagement Details

• Duration: 8 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Your customer service team spends time on tasks AI could handle: drafting initial responses, summarising conversation history, categorising requests. Each repetitive email drains capacity that could go toward complex problems.

Our Approach

1. Map communication workflows and identify pattern-based messages
2. Configure AI features with human review gates
3. Monitor quality metrics and adjust AI behaviour

Works Well When

• You use Front, Zendesk, Intercom, or Freshdesk
• You handle 50+ customer interactions daily
• Many interactions follow predictable patterns

Not Appropriate When

• Your communications are mostly complex, unique situations
• You handle highly sensitive matters (legal, medical, crisis)

Engagement Details

• Duration: 8 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Your analysts spend more time finding problems than solving them. By the time someone notices a metric drift, the damage is done. Manual report building means insights arrive too late to matter.

Our Approach

1. Connect to your data warehouse or BI platform
2. Configure statistical anomaly detection with business-relevant thresholds
3. Build automated alert and reporting pipelines

Works Well When

• You have 12+ months of clean historical data
• You use BigQuery, Power BI, Looker, or Tableau
• Your analysts spend significant time on routine monitoring

Not Appropriate When

• Your data is fragmented across disconnected systems
• You lack baseline metrics to detect anomalies against

Engagement Details

• Duration: 8 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Your team's knowledge is scattered across Notion, Google Drive, Confluence, Slack. People spend 20% of their time searching for information. Institutional knowledge lives in individuals, not systems.

Our Approach

1. Assess content landscape and quality
2. Implement AI-powered retrieval with source attribution
3. Establish governance for content maintenance

Works Well When

• You have significant documentation across multiple platforms
• Knowledge retrieval is a frequent pain point
• You can commit to content governance

Not Appropriate When

• Your documentation is minimal or outdated
• You lack capacity for ongoing content maintenance

Engagement Details

• Duration: 12 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Manual bid management doesn't scale. By the time you adjust bids based on yesterday's performance, the market has moved. Meanwhile, you're leaving money on the table with suboptimal keyword allocation.

Our Approach

1. Audit current campaign structure and performance
2. Implement AI bid strategies with human oversight gates
3. Build monitoring dashboards with automated alerts

Works Well When

• You spend £5k+ monthly on advertising
• You use Google Ads, Meta Ads, or Amazon Advertising
• You have conversion tracking in place

Not Appropriate When

• Your ad spend is too low to justify automation investment
• You lack clear conversion tracking

Engagement Details

• Duration: 10 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Content production is a bottleneck. Your team has ideas but limited capacity to execute. First drafts take hours. Editing is inconsistent. Publishing cadence suffers.

Our Approach

1. Establish content workflows with AI assistance points
2. Build prompt templates for your brand voice
3. Create quality review processes

Works Well When

• You need higher content volume
• You have clear brand guidelines to work from
• You can commit human review time

Not Appropriate When

• You expect AI to replace human content judgment
• Your content requires deep expertise AI can't replicate

Engagement Details

• Duration: 8 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Your expertise is valuable but difficult to scale. New hires take months to reach competency. Institutional knowledge leaves when people do. Clients can't access your expertise at 3am.

Our Approach

1. Knowledge extraction and documentation
2. Build custom Claude Projects or GPT assistants
3. Implement quality assurance and feedback loops

Works Well When

• You have codifiable expertise worth preserving
• You can invest 8-10 hours/week in knowledge extraction
• You understand this creates a tool, not a replacement

Not Appropriate When

• Your expertise is tacit and hard to articulate
• You expect the AI to fully replicate human judgment

Engagement Details

• Duration: 12 weeks
• Your Involvement: 8-10 hours/week
• Prerequisites: None

The Problem

AI is powerful but isolated. Your AI assistant can't access your CRM, update your project management tool, or query your database. Each integration is custom work.

Our Approach

1. Assess integration requirements and security constraints
2. Implement MCP servers for priority systems
3. Build orchestration layer for multi-tool workflows

Works Well When

• You need AI to interact with multiple systems
• You have technical capacity to maintain integrations
• Your security requirements allow system connections

Not Appropriate When

• You only need AI for conversation, not action
• Your compliance requirements prohibit system integration

Engagement Details

• Duration: 10 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

Some workflows require AI that can plan, execute, and adapt—not just respond to prompts. Sequential, rule-based automation isn't intelligent enough. You need systems that can reason.

Our Approach

1. Identify workflows suited to agentic approaches
2. Design multi-agent architectures with oversight gates
3. Build monitoring and intervention capabilities

Works Well When

• You have workflows requiring multi-step reasoning
• You can accept experimental approaches
• You have technical capacity for ongoing maintenance

Not Appropriate When

• You need guaranteed, predictable outcomes
• You're not comfortable with emerging technology risk

Engagement Details

• Duration: 16 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

AI adoption is happening with or without governance. People are using ChatGPT with company data. No one knows what's being automated. You need guardrails before something goes wrong.

Our Approach

1. Assess current AI usage and risks
2. Develop policies for acceptable use, data handling, and oversight
3. Build monitoring and compliance mechanisms

Works Well When

• You have regulatory or client requirements for AI governance
• AI adoption is accelerating without clear guidelines
• You want to enable adoption safely, not restrict it

Not Appropriate When

• You're a small team where informal governance suffices
• You want bureaucracy rather than enablement

Engagement Details

• Duration: 12 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

You're automating existing workflows instead of redesigning them. The process that made sense with 10 people doesn't make sense with AI. You're digitising inefficiency.

Our Approach

1. 20 hours of workflow observation before any proposals
2. First-principles redesign with AI capabilities in mind
3. Change management support for workflow transition

Works Well When

• You have a strategic workflow worth redesigning
• Leadership is open to fundamental change
• You can commit to proper observation before solutions

Not Appropriate When

• You want quick automation wins
• You're unwilling to question existing processes

Engagement Details

• Duration: 20 weeks
• Your Involvement: Significant
• Prerequisites: None

The Problem

You have multiple potential AI use cases competing for attention. Vendors pitch solutions. Teams request tools. Without systematic evaluation, you risk spreading resources thin or betting on the wrong use case.

Our Approach

1. Inventory potential use cases
2. Apply consistent evaluation criteria
3. Prioritise and recommend with evidence-based rationale

Works Well When

• You have multiple potential AI use cases
• You want objective assessment before committing resources
• You're willing to deprioritise based on findings

Not Appropriate When

• You've already committed to a specific direction
• You want validation for a decision already made

Engagement Details

• Duration: 3 weeks
• Your Involvement: Varies
• Prerequisites: None

The Problem

78% of AI project failures stem from poor human-AI communication, not technology limitations. Your team has access to powerful AI tools but lacks the structured approach to use them effectively.

Individual experimentation produces inconsistent results. Without shared vocabulary and methods, teams can't build on each other's discoveries. Shadow AI usage creates security risks. The gap isn't access to AI—it's capability to use it well.

The Approach

1. Foundations — Mental models for human-AI collaboration. Understanding context windows, token economics, and why prompt structure matters. The shift from "prompt engineering" to "context engineering."

2. Patterns — Practical techniques: zero-shot vs. few-shot prompting, chain-of-thought reasoning, role-based approaches, output formatting. Hands-on practice with real work tasks, not generic exercises.

3. Application — Role-specific workflows: operations (meeting summaries, documentation), marketing (content drafts, campaign ideation), analysis (data interpretation, report generation). Custom prompt templates for your recurring tasks.