Over the long weekend, I thought it might be worth underscoring a few product areas that are top of mind.
Data Integration for Regulated / Legacy Industries
I’m interested in the Fivetran model, a data infrastructure company that’s grown significantly recently. They create and maintain pre-built connectors for over a hundred common data stores, applications, etc., so customers can centralize operational data with Fivetran pipelines. Fivetran’s competitive advantage widens as they build more connectors, as well as their own internal infrastructure for quickly spinning up new integrations, hoping to take advantage of their own scale.
Most of the Fivetran connections are with stores like Snowflake or S3, which can be served across industries. Yet, there are a host of vertical-specific integrations that tend to be quite tedious and gnarly, that both initial integration and upkeep contribute to. Regulated industries also tend to have special requirements around auditing & compliance, along with software delivery — either on-prem or in a single tenant cloud. Given the scope and size of some of these industries, I sense schlep-work-as-a-service to be a source of opportunity here within life sciences, industrial, energy / utilities, government, automotive, and more. One could also wedge into building broader vertical-specific data infrastructure platforms (orchestration tool, operational database, catalog, audit log, migration & replication).
Developer-First Product Analytics
A customer is no longer singularly represented as a row in a relational database — they are instead represented as a collection of events across transaction stores. Arguably, two of the most important companies that feed into this for product analytics and events are Amplitude and Heap. Both of these tools track metrics about product usage, guiding product development and pushing users through the customer journey.
When it comes to what’s next in the market, some point to the increasingly prevalent role of engineering practices across the product development journey, especially for smaller startups going through fast iteration cycles. For example, given its emphasis on speed, integrations, and keyboard-first design, Linear is a project or task management tool built for engineers, not PMs or managers. A similar thing could happen in the product analytics space with an open source-first approach — PostHog is an example. However, primarily inspired by Segment’s Config API, I’m interested in an approach for product analytics that replaces the graphical interface with an API. In Segment’s case, they noticed customers wanted extreme extensibility, so they exposed all their data models (users, access tokens, sources, destinations, etc.) as an API. I think it’s brilliant. If developers are the ones building product, why shed one’s opinion about the web interface for a product analytics tool? Just hand over an API.
What comes in the automation universe after RPA and process mining software? I see a bit of a bimodal split. On one end, there is a developer-centric approach — give developers the libraries and frameworks to write all-powerful scripts that can automate different pieces of business software. This is what Robocorp is doing (and to a lesser extent, Walrus.ai in test automation). On the other end, work with CIOs top-down to set up an app store of common automations within a company. Given their involvement with large financial institutions, this is the approach Instabase is taking. In either case, a “library of automations” is a unifying primitive.
Gruntwork is a company I find fascinating. They offer companies access to a library of common Infrastructure-as-Code templates, along with common playbooks or recipes given the profile and characteristics of a customer. With tools like Robocorp or Instabase that allow users to design automations, is there room in the market for a vendor-agnostic automations library?
If you’re building in or interested in chatting about any of these spaces, feel free to send me a note at aashay [at] haystack.vc.