Bixel

Vectara

Vectara, Inc.·Vectara.com
Company Overview

As of July 21, 2026: Vectara is an enterprise RAG and AI agent platform with a verified 99.96% uptime over 90 days and a certification stack that clears most large-org procurement lists.

Pricing runs $100k–$500k per year across SaaS, VPC, and on-prem tiers, all contact-sales, with a 30-day free trial as the only self-serve entry point. The security posture includes ISO 27017, FedRAMP, SOC 2 Type II, and CSA STAR, plus VPC peering and private networking, which covers the controls most enterprise security reviews ask for first.

High confidence · 116 dated facts
Corroborated across 8 dimensions of the record.
uptime 90d
99.96%
Jul 2026
open roles
6
Jul 2026
integrations
9
Jul 2026
technologies
26
observed
dated changes
329
Jul 2026
The record, by dimensionevery dimension is its own page →
PricingHigh confidence · 12 dated facts
Corroborated across multiple dated, sourced facts.
Enterprise, sales-led
The range of $100k–$500k per year with no published per-seat or consumption pricing means a buyer cannot size a deal without a sales conversation; the free trial is the only way to evaluate the product before committing.
Full pricing read →
Features
RAG platform
39 stated capabilities spanning RAG, AI agents, and hybrid search, with 9 integrations; buyers should verify which integrations cover their existing data sources before assuming coverage.
High confidence · 48 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Security
Enterprise-grade
FedRAMP, SOC 2 Type II, ISO 27017, and CSA STAR are all stated certifications, and VPC peering plus audit logs are listed controls; these are company-stated claims and buyers should request the actual audit reports during procurement.
High confidence · 12 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Reliability
Dependable
The status page shows 99.96% uptime and 1 incident over the past 90 days, which is independently observable and stronger evidence than a stated SLA alone.
High confidence · 3 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Hiring
6 open roles
6 open roles split across sales and platform engineering and ML, all remote-friendly; the mix suggests the company is pushing revenue growth and product depth simultaneously, but the headcount is small enough that key-person risk on either side is real.
High confidence · 5 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Stack
Detected + stated stack
AWS is confirmed in both observed site infrastructure and job postings; Python, PyTorch, and Google Cloud appear only in job postings, so the backend runs across at least two cloud providers, which matters for buyers with cloud-specific data residency requirements.
High confidence · 27 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Positioning
AI Agent Platform
Vectara names Glean, Moveworks, and Contextual AI directly on its site and leads with 'The Enterprise Agent Platform'; buyers evaluating those three alternatives should expect Vectara to show up in the same shortlists.
High confidence · 7 dated facts
Corroborated across multiple dated, sourced facts.Full read →
Legal
Vectara, Inc.
The registered entity is Vectara, Inc., but incorporation jurisdiction, governing law, arbitration terms, and auto-renewal clauses are not stated publicly; buyers should pull these from the contract before signing.
Medium confidence · 1 dated fact
Grounded in a smaller fact set; directionally reliable.Full read →
Change History329 dated events on the record
Feature added: Custom Instructions
Feature added: Policy Enforcement
Feature removed: Custom Agent Instructions · high significance
Feature removed: Lexical Search · high significance
Feature removed: Neural Search · high significance
Security signal added: Private Networking · high significance
Feature added: Auditable Agents
Get this record via API / MCPevery field dated and sourced
RESTopen tier
GET https://api.bixel.com/v1/companies/vectara.com

{
  "data": {
    "company": {
      "name": "Vectara",
      "domain": "vectara.com",
      "categories": [
        "vector-databases"
      ]
    },
    "dimensions": {
      "reliability": {
        "facts": [
          {
            "key": "reliability.uptime_90d",
            "value": 99.96,
            "provenance": "company_stated",
            "as_of": "2026-07-20",
            "source_url": "status.vectara.com"
          },
          {
            "key": "security.cert.soc2-type-ii",
            "value": true,
            "provenance": "company_stated",
            "as_of": "2026-07-20",
            "source_url": "www.vectara.com/business/platform"
          },
          {
            "key": "pricing.tier.saas.annual_usd",
            "value": 100000,
            "provenance": "company_stated",
            "as_of": "2026-07-20",
            "source_url": "www.vectara.com/pricing"
          }
        ]
      },
      "…": "…"
    }
  }
}
MCPfor agents
# any MCP client (Claude, agents)
const record = await bixel.get_company({ domain: "vectara.com" })

# 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.