This is Part 4 of our series on Semantic Enterprise, which is part of the Creative Destruction 7 Act Play series.

In Part 1, we looked at the overall market for enterprise software to see where semantic web technology could fit. The basic conclusion: it is part of the data integration business.

In Part 2 we dove a bit deeper into the types of opportunity for semantic web vendors and how they can position to win a big share of the $229 billion enterprise software market.

In Part 3 we looked at the “gorillas”, how the big vendors are positioning for the semantic web.

In this final Part 4, we look at the other end of the ecosystem, the semantic enterprise startups.

This is Part 4 of our series on Semantic Enterprise, which is part of the Creative Destruction 7 Act Play series.

In Part 1, we looked at the overall market for enterprise software to see where semantic web technology could fit. The basic conclusion: it is part of the data integration business.

In Part 2 we dove a bit deeper into the types of opportunity for semantic web vendors and how they can position to win a big share of the $229 billion enterprise software market.

In Part 3 we looked at the “gorillas”, how the big vendors are positioning for the semantic web.

In this final Part 4, we look at the other end of the ecosystem, the semantic enterprise startups.

Categorizing Semantic Enterprise Vendors

Here are the 3 big choices that startup enterprise software vendors have to make:

1. Product or Service? Most vendors choose the services route. You don’t need much capital and it is easy to change to meet emerging technical or business requirements. These vendors create the majority of the jobs and some get to be very, very big – think Accenture or Infosys or EDS. Services startups get their break when a new technology changes the game. So lots of services companies are emerging right now that leverage their expertise in semantic web technologies.

But mostly we report on product companies. The next two choices are about what type of product.

2. End user focus or part of the IT stack? Enterprise semantic technology has typically been pitched at the middle layers of the IT stack. It is well above the operating system and database layers. But typically it is not presented as an end user solution.

Selling to IT is tricky. If your product is pitched direct to end users, you are faced with the next choice.

3. Vertical or Horizontal? The mega big opportunities are all horizontal, meaning they apply to any vertical market. Think ERP, office applications, CRM, CMS, etc. But it is incredibly hard to get traction across such a broad front. So even if the end game is a broad horizontal product, the tactical entry will often be in via vertical markets.

We will use this to categorize the semantic enterprise startups.

The StartUp List

First, apologies to those we missed! Please tell us in comments if we missed a key semantic enterprise startup.

These are mainly product companies. We are still at the phase of the market where products are emerging from services companies so we see some hybrids. But we are looking for products that comprise the majority of the revenue and that would be used by other services vendors.

• Anzo There is an open source version that originated from IBM as well as commercial version from Cambridge Semantics. This is a broad horizontal product that pitches itself as middleware and that is a tough market. But their focus on spreadsheets could be a winner. Spreadsheets are used everywhere in enterprises and desperately need some semantic structuring.

• Atigeo They are selling something called xPatterns and are keen to position it as a platform but it is hard to understand at first glance. They may have hidden strengths but need to sharpen their value proposition. They have one case study – SportsBuy – that looks like an interesting variant on recommendation engines (which are key to ecommerce).

• Collibra They position as a “data governance” vendor within the Master Data Management space. That makes sense. MDM can clearly use semantic technology. Brian Schulte explains in this article how the simple “same as” principle can overcome a lot of MDM hassles:

“Relational databases behave as if every row in a table is unique.  So when a customer database contains “IBM” and “IBM Inc.,” the system behaves as if they are two different customers.  (Then think about the work that is required to combine duplicate records).  In the world of ontologies, at least in principle, we should be able to simply declare the equivalence of the two instances and be done with it.”

 
• Expert System They position their Cogito system like enterprise search:

This is a big, mature and crowded market but Expert System has been in business for 15 years and is focusing on key markets such as Customer Care and Intelligence. Many of the early pioneers of enterprise search have been “consolidated” (aka acquired or disappeared), possibly leaving room for a new entrant.

• Franz They sell development tools and database management products.

• Hakia Enterprise Search They are taking their consumer semantic search technology into the mature market for enterprise search.

• Kyield They position as knowledge management, but we most impressed by their entry into the electronic health records market (which might be the first market where the “data locker” concept gets traction).

• Ontoprise This German company lists impressive customers, but they have a lot of products and that is not usually the recipe for success. These products may have originated from client projects, so they solve real problems, but some focus will help them to differentiate.

• Ontotext They have a similar market positioning issue as Ontoprise – too many undifferentiated products. They are part of a larger services company.

• Revelytix Their “emergent analytics” positioning may push them towards Business Intelligence, which is growing fast and driven by end user budgets. They seem to be tackling one of the most interesting challenges – how to get non-technical subject matter experts to directly create ontologies (aka taxonomies aka models).

• Talis They sell a “platform” but also have a vertical focus on education and libraries (a market that is big enough and clearly receptive to semantic web).

• Top Quadrant They also sell a broad range of development tools but have done a better job of presenting these as a suite. They also benefit from a great reference project at NASA.

———————————————————————–
CONVERT BREAKS: __default__

Categorizing Semantic Enterprise Vendors

Here are the 3 big choices that startup enterprise software vendors have to make:

1. Product or Service? Most vendors choose the services route. You don’t need much capital and it is easy to change to meet emerging technical or business requirements. These vendors create the majority of the jobs and some get to be very, very big – think Accenture or Infosys or EDS. Services startups get their break when a new technology changes the game. So lots of services companies are emerging right now that leverage their expertise in semantic web technologies.

But mostly we report on product companies. The next two choices are about what type of product.

2. End user focus or part of the IT stack? Enterprise semantic technology has typically been pitched at the middle layers of the IT stack. It is well above the operating system and database layers. But typically it is not presented as an end user solution.

Selling to IT is tricky. If your product is pitched direct to end users, you are faced with the next choice.

3. Vertical or Horizontal? The mega big opportunities are all horizontal, meaning they apply to any vertical market. Think ERP, office applications, CRM, CMS, etc. But it is incredibly hard to get traction across such a broad front. So even if the end game is a broad horizontal product, the tactical entry will often be in via vertical markets.

We will use this to categorize the semantic enterprise startups.

The StartUp List

First, apologies to those we missed! Please tell us in comments if we missed a key semantic enterprise startup.

These are mainly product companies. We are still at the phase of the market where products are emerging from services companies so we see some hybrids. But we are looking for products that comprise the majority of the revenue and that would be used by other services vendors.

• Anzo There is an open source version that originated from IBM as well as commercial version from Cambridge Semantics. This is a broad horizontal product that pitches itself as middleware and that is a tough market. But their focus on spreadsheets could be a winner. Spreadsheets are used everywhere in enterprises and desperately need some semantic structuring.

• Atigeo They are selling something called xPatterns and are keen to position it as a platform but it is hard to understand at first glance. They may have hidden strengths but need to sharpen their value proposition. They have one case study – SportsBuy – that looks like an interesting variant on recommendation engines (which are key to ecommerce).

• Collibra They position as a “data governance” vendor within the Master Data Management space. That makes sense. MDM can clearly use semantic technology. Brian Schulte explains in this article how the simple “same as” principle can overcome a lot of MDM hassles:

“Relational databases behave as if every row in a table is unique.  So when a customer database contains “IBM” and “IBM Inc.,” the system behaves as if they are two different customers.  (Then think about the work that is required to combine duplicate records).  In the world of ontologies, at least in principle, we should be able to simply declare the equivalence of the two instances and be done with it.”

 
• Expert System They position their Cogito system like enterprise search:

This is a big, mature and crowded market but Expert System has been in business for 15 years and is focusing on key markets such as Customer Care and Intelligence. Many of the early pioneers of enterprise search have been “consolidated” (aka acquired or disappeared), possibly leaving room for a new entrant.

• Franz They sell development tools and database management products.

• Hakia Enterprise Search They are taking their consumer semantic search technology into the mature market for enterprise search.

• Kyield They position as knowledge management, but we most impressed by their entry into the electronic health records market (which might be the first market where the “data locker” concept gets traction).

• Ontoprise This German company lists impressive customers, but they have a lot of products and that is not usually the recipe for success. These products may have originated from client projects, so they solve real problems, but some focus will help them to differentiate.

• Ontotext They have a similar market positioning issue as Ontoprise – too many undifferentiated products. They are part of a larger services company.

• Revelytix Their “emergent analytics” positioning may push them towards Business Intelligence, which is growing fast and driven by end user budgets. They seem to be tackling one of the most interesting challenges – how to get non-technical subject matter experts to directly create ontologies (aka taxonomies aka models).

• Talis They sell a “platform” but also have a vertical focus on education and libraries (a market that is big enough and clearly receptive to semantic web).

• Top Quadrant They also sell a broad range of development tools but have done a better job of presenting these as a suite. They also benefit from a great reference project at NASA.

———————————————————————–
• Don’t forget to propose your startup for our Semantic Web Impact Awards. The deadline is Sept. 15.

SemTechBiz is Less Than 2 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !