Case Study
AI-Enhanced Search and Knowledge Management Advisory for Industrial Manufacturing
Softwise.AI built an AI-enhanced search engine for Woodward - a global industrial manufacturer of control systems for aerospace and energy applications - delivering precision access to internal technical manuals and documents. The engagement combined data standardization across disparate information sources with a comprehensive project strategy and knowledge management advisory, helping Woodward turn a scattered technical content estate into a coherent, searchable, strategically managed asset.
CLIENT
Woodward
YEAR
2021
INDUSTIRES
Aerospace & Industrial Manufacturing - Internal Knowledge & Search
DELIVERABLES
AI-Enhanced Search Engine for Technical Manuals, Cross-Source Data Standardization, Project Strategy & Knowledge Management Advisory
The problem
Decades of engineering and operational work had given Woodward an enormous body of technical content - manuals, specifications, service procedures, internal documentation - spread across many formats, owned by different teams, and increasingly hard to search across. Engineers and operations staff needed fast, precise access to the right document at the right moment, but the existing setup had not kept pace with how the content had grown. Woodward asked Softwise.AI not only to build the search engine, but also to advise on the broader knowledge management strategy underneath it.
{Key Challenges}
Why decades of technical manuals had become harder to use, not easier?
Decades of accumulated content in many formats.
Manuals and technical documentation had grown organically across business units and product lines, with no unifying schema.
Disparate ownership across teams.
Different teams maintained their own content, with their own conventions, refresh cycles, and tooling.
Precision required in technical retrieval.
Engineering and service workflows reward the right answer; a near-miss can mean a wrong setting, a missed procedure, or a costly mistake.
No coherent knowledge management strategy.
The technical estate had been managed reactively rather than designed - the build needed to be paired with a strategy to keep it usable.
{Process}
How we built the search engine and shaped the knowledge management strategy in 4 stages?
1. Joint discovery and knowledge audit
Softwise.AI mapped the existing technical content estate alongside Woodward's teams - identifying the sources, formats, owners, and use patterns that mattered most.
2. Data standardization design
A standardization layer was designed to bring disparate sources into a coherent, queryable format - the foundation on which AI search could operate reliably.
3. AI search engine build
The search engine was built for precision retrieval across technical manuals and documentation - tuned to the language and structure of engineering content rather than generic business prose.
4. Knowledge management advisory and rollout
Alongside the build, Softwise.AI delivered a project strategy and knowledge management advisory - giving Woodward a sustainable framework for maintaining, governing, and extending the content estate after rollout.
Solution
AI-enhanced search engine for technical manuals
A precision search engine purpose-built for engineering and operational content, returning the right manual or section without forcing users to navigate folder hierarchies.
Comprehensive data standardization
A unification layer bringing technical content from disparate sources into a coherent format - making integrated search possible without imposing a single content standard on every team.
Project strategy and knowledge management advisory
A strategic layer alongside the build - covering how Woodward should structure, govern, maintain, and evolve its knowledge estate over time, so the search engine kept getting more useful, not less.
{Results}
A precision AI search engine for Woodward's internal technical manuals and documents.
A standardized data foundation spanning disparate content sources.
A knowledge management strategy for sustaining and extending the estate after go-live.
A coherent operating model for ongoing technical content governance.
{Business impact}
Faster engineering and service answers. Staff found the right manual or procedure in seconds instead of minutes - or longer.
Lower risk of operational errors. Precision retrieval reduced the chance of acting on the wrong document version or section.
Knowledge that improves with use. A managed estate kept getting more usable as content was added and updated.
Technology investment de-risked. Pairing the build with strategy meant the platform was set up to stay useful, not become the next legacy tool.
{Key recommendations}
Pair the build with the strategy. A search engine on top of an unmanaged content estate gets worse over time.
Standardize the data before adding the intelligence. Consistency at the source is what makes AI search reliable.
Optimize for precision in technical retrieval. Engineering and service workflows do not tolerate fuzzy results.
Treat knowledge management as an operating discipline, not a one-off project.
SUMMARY
Softwise.AI delivered an AI-enhanced search engine for Woodward's internal technical manuals and documents, paired with a project strategy and knowledge management advisory - turning a scattered estate of decades-old engineering content into a coherent, searchable, strategically governed asset that supports faster, more accurate engineering and service work.