In most enterprise systems, every search query is treated identically. It doesn’t matter if you’re troubleshooting a production incident or seeking a conceptual definition—the scoring function behaves the same way. The result is a messy compromise that rarely delights any audience.
Three users with three very different needs:
"error ORA-12345 in invoice processing"
Needs: Precise error matches, remediation steps, recent fixes
"What is accounts receivable aging?"
Needs: Conceptual explanations, definitions, related concepts
"How to configure automated payments"
Needs: Step-by-step guides, recent procedures, prerequisites
Traditional approaches force you to choose: optimize for keywords (missing conceptual matches) or optimize for meaning (missing exact technical terms). Manual tuning takes weeks and still produces mediocre results for some query types.
Search That Understands Intent
We built a search system that automatically detects query intent and adjusts its behavior accordingly—all configured through simple, declarative policies written in plain English.
See How Intent Changes Search Behavior
Toggle between real-world queries and watch the weighting engine adapt instantly.
Example Query
"error ORA-12345 in invoice processing"
Automatic Behavior
Prioritizes exact error codes and recent solutions
Dynamic Weights
Keywords
60%
Meaning
30%
Recency
10%
Pattern Recognition
Automatically detects query patterns to identify troubleshooting, definitions, procedures, and navigation intents.
Dynamic Weighting
Adjusts the balance between keyword matching, semantic understanding, and recency based on detected intent.
Domain Awareness
Prevents cross-contamination between domains, ensuring finance queries never return HR answers.
Configuration in Plain English
Unlike traditional search engines that require complex scoring functions or ML expertise, CoderSwap’s intent-aware search is configured through simple, declarative policies.
Traditional Approach
Complex, error-prone, requires expertise
CREATE FUNCTION custom_score(
query VARCHAR2,
doc_vector VECTOR,
metadata JSON
) RETURN NUMBER AS
BEGIN
-- 200+ lines of SQL...
-- Manual weight tuning...
-- No intent detection...
END;CoderSwap Intent-Aware Policy
Declarative, explainable, production-ready
intent "troubleshooting" when query contains error OR code
weight keywords = 0.6
weight meaning = 0.3
weight recency = 0.1
bias domain = moduleThe Technical Innovation
Behind the simple interface lies sophisticated engineering that makes intent-aware search both powerful and safe.
Declarative Policy System
Instead of writing code, you describe what you want in plain English. Our AI translates these requirements into optimized search configurations that understand context and intent.
You write: "We need precise technical search for Oracle ERP documentation. Error codes should match exactly, procedures should be recent, and results should stay within the queried module."
System creates: Intent detection + dynamic weight adjustment + time-decay scoring.
Hybrid Search Architecture
Combines multiple search signals—keywords, vectors, metadata, and recency—with weights that automatically adjust based on query intent. No manual tuning required.
Keywords
Exact matches for technical terms
Vectors
Semantic understanding
Metadata
Domain and module context
Recency
Time-sensitive content
Safety-First Design
All search configurations are validated and compiled to safe, parameterized queries. No code execution, no injection risks, no performance surprises.
Real-World Results
When ETSquare AI implemented intent-aware search for their GenAI SQL Copilot serving 20,000+ Oracle ERP schemas, the results exceeded expectations.
Before Intent-Aware Search
- Query Accuracy65%
- Wrong Domain Results12%
- Setup Time3 weeks
- Manual TuningConstant
After Intent-Aware Search
- Query Accuracy90%
- Wrong Domain Results<5%
- Setup Time5 minutes
- Manual TuningZero ongoing
Implementation Path
Connect Your Corpus
Point CoderSwap to your documentation, knowledge bases, or data warehouse. We handle ingestion, chunking, and embedding automatically.
Describe Your Search Needs
Tell us in plain English how search should behave for your use case. Our AI analyzes your corpus and generates an optimized configuration.
Test and Deploy
Test with real queries to see intent detection in action. When satisfied, generate your API key and integrate with a single line of code.
curl https://api.coderswap.ai/v1/search \
-H "X-API-Key: YOUR_KEY" \
-d '{"query": "your search query"}'Why Intent-Aware Search Matters
The difference between good and great search isn't about having more data or better algorithms—it's about understanding what users actually need. Traditional search engines force users to adapt their queries to the system's limitations. Intent-aware search adapts to users.
For enterprises dealing with complex technical documentation, this isn't just a nice-to-have. When a production system is down and engineers are searching for solutions, every second counts. When new employees are onboarding, finding the right conceptual overview matters more than keyword density.
By automatically detecting and adapting to query intent, we're not just improving search results—we're fundamentally changing how knowledge workers interact with information systems. The search engine becomes a partner that understands context, not just a pattern matcher.
"CoderSwap's intent-aware search transformed how our developers find information. What used to take minutes of digging now surfaces instantly with the right context."
Ready to try intent-aware search?
Connect your data, describe your ideal search experience, and launch a production-ready, intent-aware search pipeline in minutes.