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akta.pro
Private company data and signals API for the agent economy
618 followers
Private company data and signals API for the agent economy
618 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.
akta.pro
@subhash_kanagamani event triggers are customizable to the extent you can choose from 100+ categories (fundraising, hiring, layoffs, partnerships, office expansion etc.) of events for your company or industry/topic search. Further apply multiple filters like geo, sentiment, timeline etc. or entity filters like products, custom event, products etc.
Would love to see webhooks for specific company events eventually. That could make the outbound automation possibilities huge. What do you think?
akta.pro
@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?
Can users define their own triggers or signals based on the type of companies they’re tracking?
akta.pro
@dustin_warren Yes, that's the intended way to use it. Filtering happens at the query, so you define what counts as a signal rather than picking from preset alert types.
You can filter across a 70+ category news taxonomy, plus IAB and IPTC codes, and scope it to whatever set of companies you're tracking. So a fintech watchlist filtered to funding and leadership changes, and a separate one for competitors filtered to product launches, are just two different queries against the same endpoint rather than two different products.
Polling frequency is yours to set, and credits are only charged on news actually returned. Empty polls cost nothing, so you can run a tight loop on the things that matter without paying for quiet periods.
Webhooks for signal alerts are on the roadmap, which will remove the polling step entirely.
More data can also create more noise. How do you help users focus on the signals that actually matter?
akta.pro
Hey @evan_taft1 , completely agree, and it is the exact problem that shaped how the feed was built. More volume only helps if the processing keeps pace, so the filtering happens before delivery rather than being left to whoever consumes the feed.
Every article entering the akta.pro pipeline is entity-resolved so every company mention collapses to a single stable identifier across parents, subsidiaries, and namesakes, then scored for impact and sentiment and tagged against an 80+ event taxonomy alongside industry codes. Deduplication and the rest of the filters are configurable, so the feed can be tuned to return one clean signal per event or narrowed by impact level, sentiment, event category, entity like event, person, product or geography.
Feed definition handles the rest, whether that is a company resolved across 20M+ entities, an industry selected across 30,000+ sub-sectors, or a custom topic turned into a structured feed. The signal space ends up defined by the question being asked, which keeps the irrelevant volume out by design.
Nas.com
How do you handle companies with very limited public information?
akta.pro
@nuseir_yassin1 for such instances we rely on alternative data such as social media, blogs, podcasts etc. if there is limited information the company itself. We leverage a smart validation logic - if company has very limited public data, not all parameters are populated - only the one's which can be backed by sufficient data are populated while others are left out. Prioritizing accuracy and fidelity yet retaining good fill rates.
Cool. Can you set up notifications when a specific signal is triggered? And can you create custom signals?
akta.pro
@natalia_iankovych Custom signals, yes. Filtering happens at the query rather than from a preset list of alert types, so you define what counts as a signal. Filter across a 70+ category news taxonomy, plus IAB and IPTC codes, scoped to whatever set of companies you're tracking. So a watchlist filtered to funding and leadership changes, and a separate one for competitors filtered to product launches, are just two queries against the same endpoint.
On notifications, webhooks for signal alerts are on the roadmap. Until then you poll the news API on whatever frequency suits you, and credits are only charged on news actually returned, so empty polls cost nothing and you can run a tight loop without paying for quiet periods.
This is great. Congrats, Siddhant and team.
Since those are synthesized rather than reported data, would I be able to see what a given moat call was drawn from, or do I take the field as given?
akta.pro
@tmaleh_ Fair question, and and the short answer is you can see what it was drawn from.
Moat isn't returned as a single verdict. competitive_moat comes back as an array of typed entries, each tagged to a category, distribution advantage, switching costs, network effects, cost advantage, ecosystem lock-in, data advantage, with the specific reasoning attached to each. So you can see which dimensions are actually carrying the call and which are thin.
It also sits inside a broader company_assessment section, alongside strengths, weaknesses, key risks and key highlights. Those are fully source-traced, each entry carrying links to what it was drawn from, and the moat read is the analysis layered on that same evidence base. So the reasoning is inspectable by looking at what it was built from.
We built source traceability into the architecture itself. Any output meant for diligence has to be something you can audit back to what produced it.