Overview
A specialist B2B firm had no shortage of expertise. The problem was getting that expertise out of projects, presentations, proposals and people's heads and into a form marketing and sales could reuse.
We redesigned the path from expert knowledge to commercial content so subject-matter experts could contribute once, marketing could reuse trusted material repeatedly, and AI could help with transformation without becoming the source of truth.
Who This Is For
Engineering consultancies, technical advisers and specialist professional-services firms where the strongest commercial asset is what experienced people know, but producing content repeatedly competes with billable work.
Typical symptoms include:
- Marketing repeatedly chasing experts for input
- The same customer questions being answered from scratch
- Strong material disappearing into proposals and project files
- Thought leadership depending on a few willing individuals
- Technical reviewers spending time correcting prose rather than validating facts
- Sales teams unaware of useful content that already exists
The Situation
The firm was rich in expertise but poor at turning that expertise into reusable organisational knowledge.
A customer question might be answered brilliantly in a meeting. A similar explanation might appear in a proposal six weeks later. Marketing might then interview another expert for an article on essentially the same subject.
Each output was treated as a new content job.
The result was predictable: experts became a production bottleneck, marketing struggled to maintain momentum, and useful knowledge remained tied to the person or document that originally contained it.
AI writing tools did not solve this. They made it easier to create more text, but they did not establish which technical claims were trusted, current or reusable.
Where the Workflow Breaks
The expensive part was not writing. It was repeatedly extracting and validating the same expertise.
Our Approach
Map recurring knowledge demand
Start with the questions customers, prospects and sales teams repeatedly ask. Cluster them around problems, decisions, risks, methods, applications and evidence rather than around a publishing calendar.
Capture knowledge as knowledge
Create structured expert records containing:
- Core explanation
- Important claims
- Evidence
- Examples
- Caveats
- Audience
- Applicability
- Expert owner
- Review date
- Related services and customer problems
Change the SME role
Experts validate facts, reasoning and nuance. They should not need to line-edit every derivative asset.
Build a transformation workflow
Approved knowledge can feed:
- Website pages
- Articles
- Sales enablement
- Proposals
- FAQs
- Webinar briefs
- Social content
- AI retrieval
- Internal knowledge tools
Close the loop
Search behaviour, CRM conversations, sales objections and content performance feed a knowledge backlog showing what needs to be created, improved or retired.
Before → After
Where AI Helps
AI can:
- Extract candidate knowledge from approved source material
- Classify content
- Identify duplication
- Suggest related knowledge
- Produce first-pass channel variants
- Summarise approved material
- Identify gaps from search and sales questions
Humans remain responsible for:
- Technical truth
- Commercial judgement
- Evidence
- Sensitive claims
- Final authority
- Exceptions
What Changes
- A growing bank of reusable expert knowledge
- Less repeated SME extraction
- Clearer ownership of technical claims
- More consistent commercial content
- Faster reuse across channels
- Better support for sales
- A safer foundation for AI-assisted production
These are the operational changes the work aims for. Any measures are agreed against your own baseline during scoping.
What This Demonstrates
ECM.DEV is not simply adding an AI writer to an existing marketing process.
The intervention changes the unit of work from producing another asset to building reusable organisational knowledge.
Relevant experience
Named projects that show parts of this approach in practice. They evidence the underlying experience; none of them is the scenario above, and each case study says how it was delivered.
- Core Website Copywriting for a Robotics & Automation Engineering Company
Turning deep engineering capability into language an industrial buyer could act on, working from the engineers' own knowledge.
- Website Copy & Customer Case Studies for a Scandinavian EdTech Company
Interview-based case studies: capturing what people said once and turning it into reusable evidence.
- Website Content & Thought Leadership for an M2M/IoT Connectivity Provider
Bilingual website copy and an eight-part thought-leadership series for a specialist technical provider.
- Content Strategy & CMS Migration for a Professional Association
Content strategy for a large association of engineers and technologists.
At a glance
Client type
Capabilities
- Knowledge capture
- SME workflow
- Structured content
- AI-assisted production
- Governance
Most relevant to
Engineering consultanciesRelated patterns
Turning Customer Questions Into a GTM System
Specialist professional-services firm
Instead of inventing another editorial calendar, we used the questions prospects were already asking to build a structured knowledge backlog connecting expert answers, content, services and sales conversations.
Building an AI-Ready Content Operating Model
Mid-market or PE-backed B2B organisation
The organisation wanted more AI. The real blockers were unclear ownership, inconsistent sources and undocumented workflows. We made the process explicit first, then identified where AI could safely remove work or improve decisions.
Recognise this problem?
We can start by mapping the workflow, finding the bottleneck and defining a contained first improvement.
Discuss a first project