Package pull
9.4M/30d
Across 3 of 6 tracked companies
Category read
Transcription
AI-Buzz tracks 6 Transcription companies. Current signals are clearest in package pull, public code usage, and downstream package usage. Current leaders include Deepgram, AssemblyAI, and Gladia. The current snapshot covers 9.4M package downloads per month and 146 public importing repos.
3 of 6 companies with package pull2 of 6 companies with public code signals
Companies
6
Core companies in scope
Package pull
9.4M/30d
3 companies with registry activity
Public code
146
2 companies with imports detected
Dependents
319
3 companies with downstream packages
Funding
$333M
6 companies with disclosed rounds
Lead signals
What shows up first in this category
package pull, public code usage, and downstream package usage are the clearest aggregate signals across Transcription right now.
Package pull
9.4M/30d
3 of 6 companies show registry usage; Deepgram currently leads.
Public code
146
2 companies show public imports; Deepgram leads.
Dependents
319
3 companies show downstream package usage.
Reading
How the current signals read
package pull and public code are the clearest category-wide signals right now.
Public code
146
2 companies with imports detected
Dependents
319
Across 3 companies with downstream packages
Funding
$333M
Across 6 companies with disclosed rounds
Key facts
- Deepgram is the current DAI leader at 54.
- Deepgram leads current package pull with 5.4M/30d.
- Deepgram shows the widest public code footprint with 134 importing repositories.
- AssemblyAI has the largest disclosed funding footprint at $108M.
Coverage
- 3 of 6 companies with package pull
- 2 of 6 companies with public code imports
- 3 of 6 companies with downstream package usage
- Latest category snapshot synced April 13, 2026.
Signal routes
Where to inspect this category next
Use the category summary to identify where the signal mix is strongest, then open the company pages behind it.
DAI leader
Deepgram
DAI 54
Deepgram currently leads the overall signal read in Transcription.
Funding leader
AssemblyAI
DAI 54
AssemblyAI has the deepest disclosed funding history in this group.
Research brief
Browse Research Briefs for Transcription
Use the latest published brief for the market claim, then open the company pages that reinforce or challenge it.
Open research →Company routes
Read the strongest company pages next
These cards surface the strongest signal mixes, then link straight into the company pages with the underlying detail.
Moderate
5.4M/30d package pull, 134 public repos, and 144 dependents.
DAI
54
Package pull
5.4M/30d
Public code
134
Dependents
144
418 GitHub stars
Open company page →Moderate
4.0M/30d package pull, 12 public repos, and 172 dependents.
DAI
54
Package pull
4.0M/30d
Public code
12
Dependents
172
202 GitHub stars
Open company page →Moderate
22.3K/30d package pull, 3 dependents, and $20M funding.
DAI
29
Package pull
22.3K/30d
Dependents
3
Funding
$20M
Limited repo-health coverage
Open company page →$37M funding and 44/30d HN mentions.
DAI
0
Funding
$37M
HN
44/30d
Limited repo-health coverage
Open company page →Moderate
$19M funding.
DAI
0
Funding
$19M
2 GitHub stars
Open company page →$63M funding and 1/30d HN mentions.
DAI
0
Funding
$63M
HN
1/30d
Limited repo-health coverage
Open company page →Trend lines
How the category has been moving
View:
Hacker News discussion
Total tracked HN mentions across companies in this category over time.
30-day trend↑ +169.2%
HN Mentions grew from 26 to 70 (+169.2%) over the last 30 days.
Source: Algolia HN Search API | Methodology | CC-BY-NC 4.0
View data table
| Date | hn mentions |
|---|---|
| Jan 31, 2026 | 26 |
| Mar 2, 2026 | 2 |
| Apr 1, 2026 | 74 |
| Apr 6, 2026 | 70 |
Disclosed funding
Cumulative disclosed funding raised by companies in this category over time.
30-day trend
Total Funding reached $333M over the last 30 days.
Source: Public records | Methodology | CC-BY-NC 4.0
View data table
| Date | funding |
|---|---|
| Jan 31, 2026 | $0 |
| Mar 2, 2026 | $333M |
| Apr 1, 2026 | $333M |
| Apr 6, 2026 | $333M |
All 6 companies in this category
Comparison table
Compare the full category
Sort by the signal that matters most for this category: combined DAI, package pull, public code adoption, hiring demand, or funding depth.
| Company | DAI Score ▼ | Downloads (30d) | Public Code | Hiring | Funding |
|---|---|---|---|---|---|
| Deepgram Speech-to-text API. Fast and accurate transcription for developers. | 54 | 5.4M | 134 | - | $86M |
| AssemblyAI Speech AI platform. Transcription, summarization, and audio analysis. | 54 | 4.0M | 12 | - | $108M |
| Gladia Enterprise speech-to-text API with speaker diarization | 29 | 22.3K | - | - | $20M |
| Rev AI-powered transcription, captioning, and subtitling services | - | - | - | - | $37M |
| Fireflies.ai AI meeting assistant that transcribes and summarizes calls. | - | - | - | - | $19M |
| Otter.ai AI meeting assistant for real-time transcription and summaries | - | - | - | - | $63M |
FAQ
Common questions
What are the top Transcription AI companies?
The current DAI leaders in Transcription include Deepgram (DAI 54), AssemblyAI (DAI 54), and Gladia (DAI 29). Use the company pages to inspect the package pull, public code, hiring, and funding signals behind those rankings.
How much public adoption shows up in Transcription?
Across 6 tracked companies, current public signals show 9.4M package downloads per month, 319 known dependents, and 146 public importing repos. Coverage is uneven by company, so the detail pages show which signals are actually present for each one.
How much funding have Transcription AI companies raised?
Transcription AI companies disclose $333M in combined funding across 6 tracked companies with known rounds.
How much developer discussion shows up around Transcription?
The current snapshot tracks 70 Hacker News mentions across 5 companies in Transcription. Discussion is supportive context rather than the lead signal.
Where should I start when reviewing Transcription?
Start with the strongest signal routes: Deepgram leads package pull and Deepgram leads public code usage. Then compare those companies against the full table to see whether the category is concentrated or broad.
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