De-Risk Your AI Investment With a Structured 4-Week Discovery
Comprehensive assessment of your systems, AI opportunities, technical architecture, and business case.
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A Structured 4-Week Assessment
A structured discovery process eliminates strategy risk. We conduct a deep-dive diagnostic covering four critical dimensions of your enterprise logic.
Current State Analysis
What's your current state? Which processes are manual, which are broken, and which could be automated today?
AI Opportunity Mapping
Where does AI add value? Which problems can AI solve for your firm that couldn't be solved before?
Technical Architecture
What's your technical architecture? Defining AI models, private infrastructure, and deep integrations.
The Roadmap to Execution
The output of this 4-week diagnostic is a detailed 90-day roadmap that you understand, approve, and are confident will deliver value.
Current State Assessment
Week 1 is interviews and audits. We work with your team to understand the current state, mapping every stakeholder pain point and technical bottleneck.
Stakeholder Interviews
We interview 12 to 18 stakeholders across finance (CFO, Controller), operations (COO, managers), sales (VP Sales), and technology (CTO, infrastructure). We ask: What processes take the most time? Where do errors happen most? What systems do you use (CRM, ERP, accounting, etc.)?
System Audit
Technical audit of systems (Zoho, SAP, etc.). We review configurations, API capabilities, and data volume. We generate a data quality assessment: records with critical fields and integration health.
Process Documentation
We map your top 5 to 10 processes: onboarding, invoice processing, lead management. We document cycle time, error rates, and labor costs. Deliverable: Current State Assessment Report (30 to 40 pages).
AI Opportunity Mapping
Week 2 is creative and strategic. Given the current state, where does AI create the most material value?
Can we build it? We assess data, technical requirements, and current AI capabilities.
How long to deliver? Ranges from 8 to 12 weeks for simple automations to 16 to 24 weeks for complex integrations.
Do we have the data history? Missing data increases both timeline and implementation cost.
Constraints for FCA (audit trails) or GDPR (dataroom residency). Managed via private model deployments.
Architecture & Technology Design
Week 3 is technical deep-dive. For the top 3 to 5 opportunities, we design the technical solution.
Model Selection
For each opportunity, which AI model? Claude (reasoning-heavy tasks), GPT-4o (conversation, structured output), Gemini (multimodal, Google ecosystem), open-source (latency-sensitive, privacy-critical). We benchmark each model against your requirements.
Example: for contract analysis, we test Claude and GPT-4o on 20 sample contracts, measure accuracy, measure cost, measure speed. We quantify trade-offs.
Architecture Design
We specify: which APIs, which databases, which integrations, latency requirements (lead scoring should complete in <2 seconds), error handling (if Claude API fails, what's the fallback), monitoring (how do we know if agent is working), auditing (compliance trail).
Data Pipeline Design
For models that need historical data (churn prediction, forecasting), we design data pipelines: which data sources (your CRM, ERP, data warehouse), how often to refresh (daily, hourly, real-time), which data transformations (cleaning, normalisation, feature engineering), where to store (S3, database, vector store).
If we do, cost and timeline increase. We give you the choice.
Infrastructure Design
Where does this run? Cloud-hosted (AWS, Azure, Google Cloud) costs less operationally but requires cloud management. Self-hosted (on your infrastructure) gives you more control but requires ops team. We typically recommend cloud-hosted for UK enterprises (AWS UK region for data residency), with managed services where possible (RDS for databases, ECS for containers, CloudWatch for monitoring) to minimise ops burden.
Technical Architecture Document
Typically 40 to 60 pages. Includes: for each top opportunity, system architecture (flowcharts, component diagrams), technology stack (LLMs, APIs, databases), infrastructure diagram, security specification, and integration specs.
Implementation Timeline 8 to 14 weeks typical
Strategic clarification
001Why is discovery valuable instead of just jumping to implementation?
Discovery forces strategic clarity: you agree on which problems to solve before starting.
002How much time does this require from our team?
Minimal disruption; most people contribute only 1 to 2 sessions.
003What if the roadmap says don't do AI yet?
Or: your business is so seasonal that benefits are marginal until you fix the season forecasting manually. In these cases, we recommend: (a) do this prerequisite work first, then revisit AI in 6 months, or (b) do a small pilot to build confidence. Most enterprises find at least one high-value opportunity; few find zero.
004Can we see examples of discovery findings for similar companies?
We can show you anonymised examples (financials, metrics) but not client names or sensitive details. Ask us during the initial call; we'll share relevant examples.
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