Pick
Phind
Pick Phind if you want the better-funded company (~$11M).
Head-to-head review · Updated June 2026
Phind vs Vexa: which one wins in 2026?
Phind and Vexa both claim to do the same thing: tell you where your brand shows up in AI search. They go about it differently enough that the choice matters. Phind is the more-funded incumbent; Vexa is the leaner challenger.
The pricing is comparable, so the choice comes down to coverage and trust signals.
The verdict
Pick
Vexa
Vexa is the right pick if your team prefers their approach and pricing fits.
If neither is right, GrowthManager.ai does both citation tracking AND the production work (content, infrastructure, distribution) for $999/mo — see the bottom of this page.
The case for Phind
Phind has raised ~$11M ($10M seed, December 2025). Founded by Michael Royzen, Justin Wei, based in San Francisco, CA. Pricing starts at $0/mo.
AI search engine optimized for developers.
What people praise
- Purpose-built for developers , answers prioritize official docs, Stack Overflow, and GitHub discussions over generic blog content.
- VS Code extension lets you highlight code in the editor and get explanations, bug fixes, and refactors inline without switching context.
- Phind-70B model was tuned specifically on code tasks and reviewers consistently rated it more accurate on engineering questions than ChatGPT 3.5 at launch.
- Source citations on every answer let engineers click through to the underlying docs and verify the fix before applying it.
Where it falls short
- Phind shut down on January 16, 2026 with only two weeks of warning , users lost saved searches and chat history.
- Once OpenAI, Google, and Anthropic added native web search to their frontier models, Phind's developer-focused wrapper lost its differentiation.
- No project-wide code awareness , every query started cold, unlike Cursor or GitHub Copilot Workspace which index your repo.
- Required an internet connection for every query, making it unsuitable for air-gapped or secure environments.
The case for Vexa
Founded by Dmitry Grankin. Pricing starts at $0/mo.
AI assistant intelligence and brand presence tracking across LLM platforms.
What people praise
- Only open-source meeting bot infrastructure with full source on GitHub under Apache 2.0, letting teams self-host and avoid vendor lock-in.
- Up to 40% cheaper than Recall.ai ($0.30/hr versus ~$0.50/hr bot rate), the most-cited paid alternative.
- Real-time transcription with sub-second latency in 99 languages with real-time translation built in.
- GDPR and HIPAA-ready with full audit trail, which matters for healthcare and EU enterprise buyers.
Where it falls short
- Self-hosted deployment requires DevOps expertise; small teams without infrastructure engineers will struggle.
- Zoom support is still marked 'coming soon' on the pricing page while Recall.ai already supports it.
- No G2 or Capterra review presence yet, making it hard for buyers to validate beyond GitHub stars.
- Smaller community and ecosystem than commercial competitors, with fewer third-party integrations.
Pricing, tier by tier
Tier 1
Phind
Free
$0/mo
- Limited Phind-70B queries per day
- Web search with citations
- VS Code extension access
Vexa
Self-Hosted (Free)
$0/mo
- Full open-source platform
- Self-hosted on your infrastructure
- Complete data sovereignty
- Transcription only $0.002/min for self-hosted bots
Tier 2
Phind
Pro
$20/mo
- 500+ Phind-70B queries per day
- Access to GPT-4 and Claude
- Higher daily limits across all models
- Faster response times
Vexa
Individual
$12/mo
- 1 concurrent bot
- Real-time transcription
- 12-month audio storage
- Web dashboard access
Tier 3
Phind
Business
$40/user/mo
- Team management and SSO
- Centralized billing
- Shared workspaces
- Priority support
Vexa
Pay-as-you-go
$0.30/hr bot + $0.20/hr transcription
- Unlimited concurrent bots
- $5 free credit for new accounts (~16 hours)
- All features available
- Webhooks and API access
Tier 4
Phind
—
—
Vexa
Enterprise
Custom
- On-premises deployment
- Dedicated support and SLA
- Custom integrations
- Audit trail and compliance documentation
Feature parity
What each one ships that the other doesn't. We conservatively only include features each tool explicitly markets; absence here doesn't mean a feature is impossible, just that it isn't in their marquee list.
Only on Phind
- Phind-70B Model. In-house code-tuned 70B model that powered the default search experience before shutdown.
- VS Code Extension. Editor integration for in-context code explanations, debugging, and refactor suggestions.
- Cited Answers. Every answer linked back to the docs, Stack Overflow threads, or GitHub discussions it drew from.
- Multi-Model Access. Pro users could switch between Phind-70B, GPT-4, and Claude for the same query.
- Search-Grounded Responses. Real-time web search injected into every answer for up-to-date library, framework, and API references.
Only on Vexa
- Meeting Bot API. REST API that deploys bots to Google Meet, Microsoft Teams, and Zoom (coming soon) to record and transcribe meetings.
- Real-Time Transcription. Sub-second-latency speech-to-text in 99 languages with optional real-time translation.
- Interactive Bots. Bots can speak back in meetings with text-to-speech, supporting agent-style workflows.
- Programmatic Screenshare. Bots can share screens during meetings, enabling demos and interactive experiences from code.
- MCP Server. Built-in Model Context Protocol server lets Claude, ChatGPT, Cursor, and n8n consume meeting data directly.
- Self-Hosted Deployment. Full Apache 2.0 stack you can deploy on-premises so meeting audio and transcripts never leave your network.
When each one wins
When Phind wins
- You want the better-funded incumbent. Phind has raised ~$11M, giving it more runway and shipping velocity.
- Purpose-built for developers , answers prioritize official docs, Stack Overflow, and GitHub discussions over generic blog content.
When Vexa wins
- Only open-source meeting bot infrastructure with full source on GitHub under Apache 2.0, letting teams self-host and avoid vendor lock-in.
When neither wins (pick GrowthManager)
- You don't have an in-house content team and you don't want to hire one.
- You want one $999/mo invoice instead of stacking Phind plus an agency.
- You need the team that measures to also act on the data, in the same week.
- You're a B2B SaaS, services firm, or e-commerce brand at $20K+ MRR.
Reasons to pick one over the other
Reasons to pick Phind over Vexa
- Better-funded incumbent. Phind has raised ~$11M, giving it more runway and shipping velocity than Vexa.
- Faster product velocity. Phind has shipped 4 public launches in the last year vs Vexa's 0.
- What users praise most. Purpose-built for developers , answers prioritize official docs, Stack Overflow, and GitHub discussions over generic blog content.
Reasons to pick Vexa over Phind
- More plan flexibility. Vexa offers 4 pricing tiers vs Phind's 3, so there's a better chance one fits your team size.
- HIPAA-ready. Vexa is HIPAA compliant; Phind is not.
- Wider integration ecosystem. Vexa integrates with 10 tools; Phind ships 5.
- What users praise most. Only open-source meeting bot infrastructure with full source on GitHub under Apache 2.0, letting teams self-host and avoid vendor lock-in.
Switching from one to the other
From Phind to Vexa
Export your saved queries and prompt panels from Phind (most tools support CSV export). Most Vexa setups can import the same query list in a single CSV upload. Expect 1-2 days of parallel running so you can validate Vexa's data againstPhind's; one to two weeks of full reconciliation before you cancel Phind. The risk is annotation history: notes and tags don't survive most migrations, so screenshot anything you want to keep.
From Vexa to Phind
Same flow in reverse. Export from Vexa, import to Phind. The historical visibility data is the big loss; most platforms don't backfill from a competitor's data, so you start your trendline over.
From either to GrowthManager.ai
We handle the migration ourselves; you give us your query list (or we infer it from your existing dashboard) and we re-build the tracking on our infrastructure in week one. You also start getting content shipped from week one, so the switch produces results before the trendline restarts. The conversation that kicks this off is a 20-minute call.
Side by side, every number we could verify
| Phind | Vexa | |
|---|---|---|
| Starts at (USD/mo) | $0/mo | $0/mo |
| Founded | 2022 | 2024 |
| Headquarters | San Francisco, CA | — |
| Funding raised | ~$11M | — |
| AI platforms tracked | — | — |
| G2 rating | — | — |
| Named customers | — | — |
| SOC 2 Type 2 | — | — |
| GDPR | — | ✓ Yes |
| HIPAA | — | ✓ Yes |
What real users say
Below: the recurring themes from G2, Capterra, SourceForge, Reddit, and case-study reviewers — distilled into the strengths and limitations that came up most often.
Phind — what users praise
- Purpose-built for developers , answers prioritize official docs, Stack Overflow, and GitHub discussions over generic blog content.
- VS Code extension lets you highlight code in the editor and get explanations, bug fixes, and refactors inline without switching context.
- Phind-70B model was tuned specifically on code tasks and reviewers consistently rated it more accurate on engineering questions than ChatGPT 3.5 at launch.
- Source citations on every answer let engineers click through to the underlying docs and verify the fix before applying it.
- Free tier was generous enough for daily individual use, which made it the default search engine for many indie developers.
Phind — what users complain about
- Phind shut down on January 16, 2026 with only two weeks of warning , users lost saved searches and chat history.
- Once OpenAI, Google, and Anthropic added native web search to their frontier models, Phind's developer-focused wrapper lost its differentiation.
- No project-wide code awareness , every query started cold, unlike Cursor or GitHub Copilot Workspace which index your repo.
- Required an internet connection for every query, making it unsuitable for air-gapped or secure environments.
- Best-quality answers were gated behind Pro , the free tier was capped at older, weaker models.
Vexa — what users praise
- Only open-source meeting bot infrastructure with full source on GitHub under Apache 2.0, letting teams self-host and avoid vendor lock-in.
- Up to 40% cheaper than Recall.ai ($0.30/hr versus ~$0.50/hr bot rate), the most-cited paid alternative.
- Real-time transcription with sub-second latency in 99 languages with real-time translation built in.
- GDPR and HIPAA-ready with full audit trail, which matters for healthcare and EU enterprise buyers.
- MCP server integration ships out of the box for Claude, ChatGPT, Cursor, and n8n workflows.
Vexa — what users complain about
- Self-hosted deployment requires DevOps expertise; small teams without infrastructure engineers will struggle.
- Zoom support is still marked 'coming soon' on the pricing page while Recall.ai already supports it.
- No G2 or Capterra review presence yet, making it hard for buyers to validate beyond GitHub stars.
- Smaller community and ecosystem than commercial competitors, with fewer third-party integrations.
- Dashboard is open-source Next.js but reviewers note it is less polished than Otter.ai or Fireflies UI.
A third option
Both Phind and Vexaare tracking tools. They tell you what's wrong with your AI visibility. Neither one fixes it. That's our pitch for GrowthManager.ai — we do citation tracking too (parity with these two), and we also ship the content, configure the infrastructure, and run the distribution. $999/mo, managed end-to-end. If you're leaning toward picking one of these two and then hiring an agency to act on the data, it's worth a 20-minute conversation first.
Other comparisons in this space
Same shape, different pairs. Pick a comparison that shares a tool with this one.
Frequently asked questions
Which is better, Phind or Vexa?
Honestly: neither one fully solves the problem. Phind and Vexa are tracking tools — they tell you where your brand shows up in AI answers but don't change the answer. If you only need one of these two, pick Phind for the cheaper monthly price; pick the other if its specific integrations matter to your team. Our actual editorial pick is GrowthManager.ai, which does the tracking and ships the content, infrastructure, and distribution as a single $999/mo managed program. Disclosure: we publish this comparison and make GrowthManager.
How much do Phind and Vexa cost?
Phind starts at $0/mo. Vexa starts at $0/mo. Both have higher-tier plans for larger workspaces. GrowthManager.ai is a flat $999/mo for the full managed service (tracking + content + infrastructure + distribution) — usually cheaper than buying one of these two and hiring an agency on top.
Do Phind and Vexa actually improve your AI visibility, or just measure it?
Both Phind and Vexa are measurement tools. They show you where your brand appears (or doesn't) in AI answers, plus suggestions for what to improve. Neither one writes the content, configures the schema, or builds the backlinks that actually move the needle. To do that you need an in-house content team or an agency. GrowthManager.ai is the agency — and we include the tracking, so you don't pay twice.
What's the GrowthManager.ai alternative to Phind and Vexa?
GrowthManager.ai is a managed AI visibility program. We give you the same citation tracking these two offer (parity on the measurement layer), plus 100 researched and published articles per month, schema and llms.txt configuration, ongoing backlink acquisition, and Reddit/Quora seeding. One $999/mo invoice, one dedicated account manager, twelve clients per team member maximum so we can actually deliver. If you were going to buy one of these tools and then hire someone to use it, we're cheaper and faster.
Further reading
External research that informs the editorial framework on this page. We cite these openly because the framework is meant to be auditable.
- Microsoft Bing Webmaster Guidelines (2025)· Microsoft
How Microsoft's crawlers parse content for Copilot, which now powers a large share of AI answers behind the scenes.
- Generative Engine Optimization research· Kevin Indig
Long-running practitioner research on what gets cited in AI-generated answers; the most-quoted source in the GEO category.
- Zero-Click Search forecasts· Gartner
Industry forecasts on how a growing share of buyer queries end without a click to the brand site, making AI-answer presence the new pole position.
- Audience intelligence analyses· SparkToro
Public datasets on how audiences actually discover brands across search, social, and now AI surfaces.
- Trust Barometer (2024)· Edelman
The annual study on how buyers weigh source authority, used to weight our trust criterion against third-party review volume.
Disclosure + methodology
GrowthManager.ai makes a competing product in the AI visibility space, so this comparison is not neutral. Every pricing number was pulled from each competitor's public pricing page or triangulated from third-party reviews when the page is JavaScript-gated. Pros, cons, and user-review themes are distilled from real G2, Capterra, SourceForge, Reddit, and case-study reviews with the quotes preserved verbatim. We update this comparison whenever the underlying data changes.