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diff --git a/plan/duree-pitch.org b/plan/duree-pitch.org deleted file mode 100644 index 485dd39..0000000 --- a/plan/duree-pitch.org +++ /dev/null @@ -1,76 +0,0 @@ -#+TITLE: Duree: automated universal database -#+SUBTITLE: seeking pre-seed funding -#+AUTHOR: Ben Sima <ben@bsima.me> -#+EMAIL: ben@bsima.me -#+OPTIONS: H:1 num:nil toc:nil -#+LATEX_CLASS: article -#+LATEX_CLASS_OPTIONS: -#+LATEX_HEADER: -#+LATEX_HEADER_EXTRA: -#+LATEX_COMPILER: pdflatex -#+DATE: \today -#+startup: beamer -#+LaTeX_CLASS: beamer -#+LaTeX_CLASS_OPTIONS: [presentation,smaller] -* Problem -Developers spend too much time managing database schemas. Every database -migration is a risk to the business because of the high possibility of data -corruption. If the data is modeled incorrectly at the beginning, it requires a -lot of work (months of developer time) to gut the system and re-architect it. -* Solution -- Using machine learning and AI, we automatically detect the schema of your data. -- Data can be dumped into a noSQL database withouth the developer thinking much - about structure, then we infer the structure automatically. -- We can also generate a library of queries and provide an auto-generated client - in the choosen language of our users. -* Existing solutions -- Libraries like alembic and migra (Python) make data migrations easier, but - don't help you make queries or properly model data. -- ORMs help with queries but don't give you much insight into the deep structure - of your data (you still have to do manual joins) and don't help you properly - model data. -- Graph QL is the closest competitor, but requires manually writing types and - knowing about the deep structure of your data. We automate both. - -* Unsolved problems -- Unsure whether to build this on top of existing noSQL databases, or to develop - our own data store. Could re-use an existing [[https://en.wikipedia.org/wiki/Category:Database_engines][database engine]] to provide an - end-to-end database solution. -* Key metrics -- How much time do developers spend dealing with database migrations? What does - this cost the business? We can decrease this, decreasing costs. -- How costly are failed data migrations and backups? We reduce this risk. -* Unique value proposition -We can automate the backend data mangling for 90% of software applications. -* Unfair advantage -- I have domain expertise, having worked on similar schemaless database problems - before. -- First-mover advantage in this space. Everyone else is focused on making - database migrations easier, we want to make them obsolete. -* Channels -- Cold calling mongoDB et al users. -* Customer segments -- *Early adopters:* users of mongoDB and graphQL who want to spend time writing - application code, not managing database schemas. The MVP would be to generate - the Graph QL code from their Mongo database automatically. -- Will expand support to other databases one by one. The tech could be used on - any database... or we expand by offering our own data store. -* Cost structure -** Fixed costs - - Initial development will take about 3 months (~$30k) - - Each new database support will take a month or two of development. -** Variable costs - - Initial analysis will be compute-heavy. - - Following analyses can be computationally cheap by buildiing off of the - existing model. - - Customer acquisition could be expensive, will likely hire a small sales - team. -* Revenue streams -- $100 per month per database analyzed - - our hosted service connects to their database directly - - includes client libraries via graphQL - - may increase this if it turns out we save companies a lot more than $100/mo, - which is likely -- enterprise licenses available for on-prem - - allows them to have complete control over their database access - - necessary for HIPAA/PCI compliance |