AI for Software Engineering — Industry Landscape (12/Aug/2018)

AIFORSE Landscape Initial Version: 03/Oct/2017.
AIFORSE Landscape Previous Version:

It's already 10 months passed since the last update of the AIFORSE Landscape — analytical report about the actual State of the Market for Solutions, which use AI to solve Software Engineering tasks.

We are happy to publish a new version of the AIOFRSE Landscape.

At the end of the Article, you will find a reference to a spreadsheet with a list of all Solutions and References to their web pages.

Please find below the aggregated data about all the AIFORSE Solutions, distributed by two axes in the same way as it was done in previous versions of the Landscape: SDLC Phase and Maturity Level (you can read in more details below).

AI for SE Industry Landscape by AIFORSE Community.

Solutions distribution by analyzable criteria

In the table above, there are three color scales applied to the aggregated numbers in order to highlight the main trends in the Industry:

  • The most “popular” SDLC Phase, to which AI is applied— bottom row (blue color): leaders are "Code Construction / Configuration Management" and "Quality Management/ Testing", which indicates where the major part of software engineering costs is;
  • The most frequent Maturity Level of the Solution — right column (red color): the leading Level is "Landing Page", which means that the Industry still resides in its early stage of development;
  • General trend (intersection of SDLC Phase and Maturity Level) for the all the Solutions, provided in the Landscape — table body (green color): you can spot a disproportion in that for the “Quality Management/ Testing” there are more Solutions converted from just ideas to the working products rather than for the “Code Construction / Configuration Management”.

Methodology Changes

Columns Semantics

There were no changes to columns set — they still represent the SDLC Phase. Here is an excerpt from the Initial Version for the Landscape, describing these criteria:

Independent on which Software Development Methodology you use, the size of your team or type of your Product, you need to go through these Phases. We took the Software Engineering Body of Knowledge (SWEBOK) Knowledge Areas and merged some of them for few reasons. The main reason is that it is not always possible to unambiguously define which Solutions fall into which Category. Also, few of the SWEBOK Knowledge Areas were eliminated as not common and not related directly to SDLC.

Rows Semantics

Rows represent Maturity Level of the Solutions (highest row — most mature). There were changes done to this criteria: "Academic Researches" are now removed from the Landscape — new project "AIFORSE Papers" to be launched later to track this.

The actual classification is as follows.

  • [Upd] B2B Ready: there is a website for the Solution with at least two of the next information types: Customers, Demo (video/screens/code etc.), Pricing.
  • B2C Ready: the same as “B2B Ready”, but AI is applied to SE indirectly: not through Tools for Software Engineers, but directly to Software Products, used by end Customers.
  • [New] Internal Development: there are "AIFORSE " Tools which are created in big software engineering companies like FAMGA, and about which we have limited knowledge, but in any way shall be presented in the Report.
    We are calling such companies to endorse the experience sharing to intensify the Industry development.
  • Landing Page: there is only a web page with a description of a Solution, but with no information about Customers, Demo and Pricing.

Solutions List

All the Solutions are listed in the Google Spreadsheet.
It has Solution name, description, URL and extended mapping to SDLC Phases and Maturity Level, so you can use filters to locate the particular Solutions subset fast.
The file cannot be changed, but you can leave your comments in it.
The file cannot be downloaded or printed, so if you would like to get a copy, please reach out to as it info[at]

AIFORSE Landscape — ver.2018–08–12


  • The Market is growing: 43 Solutions (now) against 29 (10 months ago): +48% (comparing only sum of "B2B Ready", "B2C Ready"and "Landing Page" Solutions).
  • +12 Solutions is not an absolute growth: 5 Solutions, listed in the previous version of the Landscape, were excluded from the actual one as they do not fit entry criteria anymore; so we have 17 new Solutions.
  • Companies are looking for their niches — during last 10 months, 5 Solutions changed the SDLC Phase they cover.

If you have any comments and/or suggestions for Solutions, Categories or their mapping, please feel free to share them.

AIFORSE Landscape Initial Version: 03/Oct/2017.
AIFORSE Landscape Previous Version:

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Valentin Grigoryevsky

Valentin Grigoryevsky


System Architect, transforming Software Engineering Industry. Founder @ AIFORSE Community.