Why?
The list didn't include the three mentioned in the comments here (Attio, Twenty, Monday). My strong suggestion is that you look at the current entrants and try to find some differentiation.
Response from ChatGPT:
"CRM systems with the capability to support custom data objects are designed to offer businesses the flexibility to tailor the CRM to their specific needs, such as tracking unique customer data, industry-specific information, or customized business processes. Here are ten CRM systems known for their ability to support custom data objects:
Salesforce: Known for its high degree of customization, Salesforce allows users to create custom objects to store specific business data and relate to other records within the system.
Microsoft Dynamics 365: Offers extensive customization capabilities, including the creation of custom entities (data objects) that can be integrated seamlessly with the rest of the system.
Zoho CRM: Provides the ability to create custom modules that can be designed to capture and manage business-specific information.
HubSpot CRM: Allows the creation of custom objects to store and organize data that doesn’t necessarily fit into the standard objects like contacts or companies.
Oracle NetSuite: Features a flexible platform that includes the ability to create and manage custom records tailored to your business needs.
SAP CRM: Part of the SAP Business Suite, SAP CRM offers the flexibility to extend its core functionalities with custom objects to meet specific business requirements.
Pipedrive: Known for its user-friendly interface, Pipedrive also offers custom fields and, in some plans, the ability to create entirely custom data objects.
SugarCRM: Provides a highly customizable platform where users can create custom modules and fields to adapt the CRM to their business processes.
Insightly: Offers custom fields and records, allowing users to tailor the CRM system to better fit their specific business needs and workflows.
Freshsales (Freshworks CRM): Allows for the customization of the CRM with custom fields and modules, enabling businesses to track unique data points relevant to their operations."
- Getting to know you and your business - Deciding whether you’re worth investing more time into - Discussing with colleagues if you’d be a fit for their portfolio - Discussing valuation and terms - Them pitching your business to their investment committee - Agreeing and signing a term sheet - Legal, technical and financial DD - Final contracts and negotiation
People often fail to realise how many steps there are in a VC investment. Typically angel investors are usually faster and less formal.
This sounds good - social media feels unusual (I spent 2 years at a VC fund).
VCs, due to the nature of their business, are incentivised to keep potential investments ‘on the line’. That means it’s very rare to get a full-on rejection from a VC right at the very beginning.
Most deals never go past that initial “coffee and hello” stage.
My advice would be if you have one VC’s ears perked up… Use that as evidence you’re onto something and talk to more.
It’s very much a FOMO game - investors will always be more interested if you’re talking to other firms.
Best of luck.
Also if you're actively fundraising, run a process - you should be going down a list of like 100-200 VCs, any one intro meeting like this should mean nothing to you. Don't get emotionally attached this early in the pipeline
Granted, most nice plants still seem to require some light, but the efficiency advantages over photosynthesis still apply. So maybe use transmissive solar panels to mildly shade the plants, plus hydroponics to deliver the synthetic nutrient solution to them.
However, I would definitely not recommend raising while you're there on paper and leaving right after. This is a pretty material piece of news to leave off of a fundraise, and best case tanks your reputation going forward with investors, at worst is fraudulent and leaves the company (and perhaps you) open to legal action.
Eztra happy if it would be possibe to tune denoising, using photos from the same series. Multiframe NLMeans right now is slow and mostly theoretical.
IPFS is an alternate solution, but as addresses are not updatable someone somewhere needs to keep track of where the canonical source is. Further, there is no API built in - the data would live at some address, but someone still needs to construct a way to get it without just downloading the whole data dump at once. Perhaps you shard across different files but that has its own issues.
On chain with Ethereum, you can use a smart contract which allows CRUD operations on the data on a per item basis. The latest version of the smart contract data is clear. The API is basically set with the smart contract - infra to get that has already been built with libraries like ethers, and will continue to be maintained since there are other contracts/products out there that rely on the same infra.