akta.pro
Private company data and signals API for the agent economy
691 followers
Private company data and signals API for the agent economy
691 followers
Private company data with 4x the depth and 2x the coverage of PitchBook, plus 100+ event signals and news across companies, industries, and topics. Source and diligence deals or make outreach lists and trigger outbound. Built for financial services and GTM teams, pay-as-you-go.
Would love to see webhooks for specific company events eventually. That could make the outbound automation possibilities huge. What do you think?
@himani_sah1 Agreed, and webhooks for signal alerts is coming soon!
In the meantime polling gets you most of the way there. You can hit the news API on whatever frequency and offset suits your workflow, and credits are only charged on news actually returned.
For outbound specifically, the 86-category event taxonomy is the part worth looking at. You can filter to the handful of event types that actually trigger a play, funding rounds, leadership changes, expansion signals, rather than filtering a general feed downstream.
What use-cases on outbound automation are you looking at?
Congratulations on the launch @siddhant_masson! This is a smart angle - especially the combination of structured company data with event signals instead of forcing agents to stitch both together from separate sources. Curious - which use case are you seeing the strongest pull from right now?
@yogesh_builds Thanks Yogesh. Yes, overlaying signals on top of companies with proper entity resolution is something our team has really worked tirelessly over the last couple of years.
We see the strongest pull for the following use-cases (top 1 by segment)
1) For GTM teams - Find Companies by Signals
e.g. Find by every US Series A-D software company that announced a partnership with AWS/Microsoft/Snowflake
2) For Investors - Find notable milestones for startup pipeline in CRM
e.g., Notify me whenever any of the startups in my list have a) new product launch b) closed a big logo c) announced fundraising d) made a strategic hire e) hiring for 5 or more new jobs etc.
3) For Corporates - Competitive monitoring
e.g., Track every product launch, partnership, expansion, negative press, c-suite hiring for my top 5 competitors
@siddhant_masson Great!!
Love that you built this API-first for AI agents rather than dashboards, giving agents structured company signals to act on feels like the real unlock here.
@ilko_kacharov thanks Ilko. With API-first approach, you basically give the end user (whether developer or business) to customize their own way of digesting information. Interestingly, lot of business users are using MCP with Claude to create extremely versatile dashboards / mini-apps.
@ilko_kacharov Thanks, and that's the bet. We believe strongly that the future is headless - what matters then is whether the data arrives in a shape an agent can act on: resolve identity, deterministic schemas, signals structured. Build for that and the interface question mostly answers itself, since anyone can put whatever surface they want on top.
@istiakahmad Thanks, and that was the reasoning. Resolving at capture rather than at query time is what lets every endpoint stay sync.
That matters if you're reasoning inside an agent loop or building a platform where someone is waiting. A data call that returns a job ID and asks you to poll compounds across every step of a run. So every API is sync, no job submission, no polling. The resolution work is already done by the time you ask.
@imtiaj_ahmad that's true. For so long high quality datasets were tied to large enterprise contracts, but that doesn't work for the agent economy. Our endeavor is to provide institutional grade data with consumption based business model to lower the barrier for entry for agent developers all over the world.
Congrats on shipping! Reliable private company data through a clean API is essential for autonomous AI agents to make real decisions. Simple, high-utility infrastructure for dev teams.
@thisiskp_ Thanks! Reliable is the word that matters most there, and in practice it comes down to schema and data consistency. Same shape every call, stable field names, nulls where data genuinely doesn't exist. That means you write the parsing logic once and it keeps working, instead of defensive handling around every field that might or might not show up.
Congratulations on the launch! Private-market data definitely needed something more developer-friendly for a while. Akta seems like a great solution.
@syed_shayanur_rahman Thanks. In most legacy private markets tools the API is an afterthought. Responses come back bulky, the structuring is off, and you end up writing a normalization layer before the data is usable.
MCP usually repeats the problem. What gets exposed is a subset of the API wrapped once and shipped, so you inherit every constraint of the original surface plus a few new ones.
We built the other way round. Structured JSON with deterministic schemas, full access across every offering rather than a curated slice, and rate limits set for how agents actually query. The MCP server and CLI are designed around real workflows, not mechanical wrappers over endpoints.
Would love to hear feedback on what is working and what is not