Bixel

TopK

Topk.io
Company Overview

As of July 21, 2026: TopK is a usage-based search engine for AI applications that has posted 100% uptime over 90 days and claims 10x lower cost than alternatives by building on object storage.

The platform charges granularly across storage, compute, and document processing, with rates as low as $0.10/GiB for storage and $0.005/page for PDFs, making cost predictable at low volume but worth modeling carefully at scale. TopK holds SOC 2 Type I and names Gemini File Search and Amazon Bedrock Knowledge Base as direct comparisons, which tells you the buyer it is chasing.

High confidence · 85 dated facts
Corroborated across 8 dimensions of the record.
uptime 90d
100%
Jul 2026
open roles
2
Jul 2026
integrations
1
Jul 2026
technologies
10
observed
dated changes
50
Jul 2026
The record, by dimensionevery dimension is its own page →
PricingHigh confidence · 18 dated facts
Corroborated across multiple dated, sourced facts.
Usage-based
There is no flat monthly fee: every dimension of usage has its own rate, from $0.01 per 1k writes to $20/GiB for query memory, so a team with spiky or memory-heavy workloads should run a cost model before assuming the free-tier entry price holds.
Full pricing read →
Features
Multi-tenancy platform
Benchmarked at 124.8ms P99 latency for multi-vector queries, 176.5 QPS per replica set, and a 1.2-second index lag, with 95% recall on filtered queries; those numbers are stated by the company and no independent benchmark is cited, but they give a concrete baseline to test against.
High confidence · 33 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Security
Compliance-ready
SOC 2 and SOC 2 Type I are listed, alongside encryption in transit, encryption at rest, and RBAC; enterprise procurement teams will likely ask for Type II, which is not yet listed.
High confidence · 8 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Reliability
Dependable
100% uptime and zero incidents over the past 90 days are reported on their status page, which is currently operational; the track record is short but clean.
High confidence · 3 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Hiring
2 open roles
Only 2 open roles, both in engineering, with no remote policy stated; a very small active headcount suggests the product is either stable or the team is constrained.
High confidence · 3 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Stack
Modern web stack
The live site runs on Next.js, React, Tailwind CSS, and Vercel, which is a standard modern web stack and says nothing unusual about the underlying search infrastructure.
High confidence · 11 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Positioning
Search Engine
The homepage headline is "Store anything. Find everything." and the company names Gemini File Search and Amazon Bedrock Knowledge Base directly, so it is explicitly targeting teams already evaluating managed AI search from cloud incumbents.
High confidence · 7 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Funding
$5.5M raised
A single $5.5M Seed round is all that is disclosed; that is enough to ship a product but leaves limited runway for enterprise sales cycles or a major infrastructure buildout.
High confidence · 2 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Change History50 dated events on the record
Feature added: Vector Search
Feature added: Custom Reranking
Pricing changed: Vector Storage usage rate · high significance
Pricing changed: Document Processing Images usage rate · high significance
Pricing changed: Document Processing Pdfs usage rate · high significance
Pricing changed: Storage usage rate · high significance
Pricing changed: Document Processing Image usage rate · high significance
Get this record via API / MCPevery field dated and sourced
RESTopen tier
GET https://api.bixel.com/v1/companies/topk.io

{
  "data": {
    "company": {
      "name": "TopK",
      "domain": "topk.io",
      "categories": [
        "vector-databases"
      ]
    },
    "dimensions": {
      "reliability": {
        "facts": [
          {
            "key": "reliability.uptime_90d",
            "value": 100,
            "provenance": "company_stated",
            "as_of": "2026-07-20",
            "source_url": "status.topk.io"
          },
          {
            "key": "security.cert.soc2",
            "value": true,
            "provenance": "company_stated",
            "as_of": "2026-07-20",
            "source_url": "www.topk.io/security"
          },
          {
            "key": "hiring.open_roles",
            "value": 2,
            "provenance": "company_stated",
            "as_of": "2026-07-20",
            "source_url": "www.topk.io/careers"
          }
        ]
      },
      "…": "…"
    }
  }
}
MCPfor agents
# any MCP client (Claude, agents)
const record = await bixel.get_company({ domain: "topk.io" })

# returns the whole record above,
# each value with its source_url + as_of,
# ready to reason over
Build on the company record. One key, REST + MCP, every signal dated and sourced back to the page it came from.
How Bixel reads this

Every read above is derived from public signals, each sourced and dated, and kept honest about provenance: what the company states on its own pages and job posts (pricing, security, careers, positioning, its backend stack) versus what Bixel independently detects (technologies, infrastructure). Where a stated claim is also detected we mark it verified; where we only have the claim, we say so. Bixel infers posture: how it monetizes, how mature it is, where it's heading. It does notclaim private financials it can't observe. Where signals are thin, the confidence says so.

Public record, read from companies' own pages and boards. Every fact dated and sourced; provenance (observed vs company stated) shown inline.