On-the-Fly Entity Identification and Learning. No Technology Background Required.


A visual analytics tool for business development and strategic sales professionals, corporate leadership, and analysts, that provides an interactive visual platform for exploiting Saffron’s “analytic reasoning” methods.

SaffronAdvantage™ is designed to give you connected knowledge and decision experience from multiple data sources – internal and external – with speed and flexibility. SaffronAdvantage sits at the top of the Natural Intelligence Platform™ and gives you a wide range of solution capabilities to help you gain a competitive advantage in your industry including:

  • Information discovery and sense making visual analytics- See a 360 degree view of your data. Rapid visualization of associated entities from multiple, diverse sources.
  • “Find without knowing” what’s in the data – Find patterns and connections. Who/what is connected or similar to whom/what? How, when, where, why?
  • Analytic Methods such as connections, networks, analogies, temporal trends and episodes.
  • Similarity Analysis – Who/What/Where are things similar? Have we seen this before? Find similar customers, problems, etc.
  • Classification – Make experience-based, adaptive decisions; returns class rank based on nearest neighbor reasoning.

SaffronAdvantage and Associative Memories

SaffronAdvantage enables you to quickly form a reliable contextual awareness of key entities – such as who, what, when, where – that are relevant to a given situation. All source material – structured and unstructured – is automatically represented in SaffronMemoryBase as a massive network of memories for every entity – every person, place, and thing in your data. Each entity memory is an analytical starting point of its own, and allows the user to quickly “fly through” the entity network – discovering the associations between entities in context of who, what, when, where, how, and why they are associated. The data source evidence is also indexed to these associative memories, enabling clear “down to the sentence or snippet” level traceability for unstructured sources, and to the record level and field level for structured sources. Context-dependent, these associations allow the user to focus on what’s relevant to the search or query, rather than having to read documents or navigate the usual “balls of yarn” produced by conventional data analytics and business intelligence tools.


Standard Queries:

  • What contracts are similar to this where we have had successful results?
  • What’s similar and what’s different about prior contracts from the one in play? People, teaming partners, competitors, technology components, locations, duration, and more?
  • Which of our teaming partners are associated with our competitors? Where, When, How?
  • What problems has the customer had with prior contract awards? Where, When, Who?

Situational Awareness and Continuous Sense Making

  • What’s ‘New and Interesting” from incoming data to our opportunities
  • Past -performance similarity
  • Multi source competitive intelligence
  • Multi source customer/program political network analysis
  • Temporal associative trending e.g. BD customer contact activity

Decision Support: Should we compete, can we win?

  • Advanced queries e.g. vendor affinity, competitive ranking
  • Structured argumentation for ‘Winability” analysis
  • Collection and exporting for gate and team reviews
  • More use of temporal and geographic analysis e.g. episodic trends

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