Basis
Worth-Joining Index · Scorecard
v2.1 ALPHA · 2026-08Career Score
—/100
Coverage
51%
Verified
17%
Stage cohort
Early
Vibe Check
🎪 community voting coming soon
Latest valuation
$1.15B (Series B, 2026-02)
Total raised
$134M total raised (Series A $34M + Series B $100M)
Traction · Key numbers
Funding
Total raised
$134M total raised (Series A $34M + Series B $100M)
Rounds
3
Valuation pace
Valuation reached ~$1.15B post-money within 2-3 years of founding
$100M
Series B · 2026-02 · valuation $1.15B post (Series B, 2026-02) · led by Accel, GV (Google Ventures), Lloyd Blankfein
With: GV, Lloyd Blankfein, Khosla Ventures · Series B lead investors; existing backers Khosla Ventures etc. also participated
$34M
Series A · 2024 · led by Khosla Ventures
With: NFDG, Larry Summers, Adam D'Angelo, Jeff Dean
$3.6M
Seed · 2023 · led by Better Tomorrow Ventures
With: BoxGroup, Abstract Ventures
▸Khosla led the A and returned for the B, while Accel leads the B alongside GV and Lloyd Blankfein — a classic 'insider doubles down + new-name validates' pattern, signaling growing rather than fading conviction
▸Reaching a $1.15B valuation within 2-3 years of founding is a faster pace than most vertical AI agent startups, which reflects strong belief in the 'AI replacing licensed professional hours' thesis — but also sets a high bar for what growth must follow
▸Penetration into ~30% of the top-25 US accounting firms shows the product has cleared the compliance and accuracy bar of the most demanding buyers — a rare proof point for vertical AI in a regulated profession
Founders
Matt Harpe CEO
Former Boston Consulting Group and SoftBank executive
Mitchell Troyanovsky Co-founder
Co-founder, involved in team culture and operations
Reality · Working here
Signals & Risks
Editorial ✎
Good fit for
· Engineers who want to build high-accuracy, compliance-heavy 'AI replacing professional hours' agents — the bar here is audit-grade, not consumer-chatbot-grade
· People with patience for a 'boring but high-value' vertical like accounting/tax/audit — sales cycles with top firms are slow to build trust, but the resulting moat is real
· Those who enjoy deep integration work with large enterprise customers — the product has to embed into firms' existing workflows and data systems
Not for
· Anyone wanting fast consumer-facing iteration cycles with weekly growth experiments — customers here are conservative large firms and the pace is slower
· Anyone uncomfortable investing extra engineering effort in explainability and accuracy for regulatory/audit accountability
Ask in the interview
1. How concentrated is current revenue/customer base? What happens to retention if 1-2 top-tier firms churn?
2. Against both general-purpose LLM vendors' enterprise offerings and other accounting-AI startups, what is Basis's actual technical/data moat?
3. With valuation reaching $1.15B in 2-3 years, what growth/ARR expectations does the team feel internally, and how do they think about that pressure?
Data changelog
Community corrections → editorial review → applied, fully on the record
data as of 2026-02 · Source: SiliconANGLE ↗
data as of 2026-02 · Source: SiliconANGLE ↗
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