Voiceops, Inc.

Name: Voiceops, Inc.
Brand: Voiceops, Inc.
Rating: 5 (3 reviews)

We help B2C companies listen to their customers at scale.

Est 2016|Valuation $26M|Raised $23.7M|12 Ref Customers

LinkedIn 5K|Website|FTEs 13|HQ New York, New York, US

MarketsCS Quality Management & Coaching Conversation Intelligence

01Competitive Landscape

Narrative analysis

- Direct competitors and their differentiators - Voiceops vs Observe.AI - Both vendors focus on scaling QA and extracting intelligence from conversations. Observe.AI is frequently discussed as a broader contact-center-focused suite, while Voiceops presents itself as focused on structured data extraction and workflow automation from conversations. - Voiceops vs CallMiner - CallMiner emphasizes established enterprise deployments and clearer guidance on pricing structures tied to users or interaction volume; Voiceops’ pricing is less transparent publicly. - Feature comparison: areas of comparative strength and uncertainty - Potential Voiceops strengths (vendor-stated) - Dynamic schema updates as new signals are identified. - Focus on pushing structured outputs into operational workflows (CRM fields, alerts). - Potential gaps / unknowns - Public documentation about enterprise governance features (RBAC, audit logs, data retention) is limited. - Multi-channel parity (chat/email/SMS) versus voice-first capabilities should be validated in pilots. - Pricing comparison: value proposition vs alternatives - Most enterprise conversation intelligence tools are sales-led and require commitments; ROI validation via pilots and reference checks is recommended. - Customer testimonials comparing this product to competitors - No independent customer comparisons were located in the accessible sources. - Market share and adoption trends - No quantitative market share data for Voiceops was found in the sources reviewed. The vendor lists customer logos on some pages; these are not a substitute for quantified adoption metrics.

	Voiceops	Observe.AI	CallMiner
Starting Price	Sales-led, custom pricing (no public tiers)	Sales-led, custom pricing (no public tiers)	Sales-led bundled pricing based on users or interaction volume
Best Fit	Mid-market/enterprise B2C teams seeking structured conversation data and workflow outputs for QA, compliance, and operational automation	Contact centers seeking an integrated suite with agent assistance, QA, real-time coaching, and analytics	Mid-to-large contact centers focused on enterprise-grade conversation analytics and VoC programs
Key Strength	Vendor emphasizes dynamic schema updates, creation of custom extractors, multilingual support, and workflow outputs into operational systems	Broad platform depth in contact center AI, including real-time assist and agent workflows	Established enterprise deployments with pricing approaches tied to volume or users; strong analytics focus
Key Weakness	Limited independent review footprint; publicly available security/compliance documentation is limited; pricing is not transparent	Also sales-led pricing and may require larger minimum commitments depending on scope	Can be heavyweight to implement for smaller teams; pricing is typically sales-led

01Competitive Landscape

Narrative analysis

Direct competitors and their differentiators
- Voiceops vs Observe.AI
  - Both vendors focus on scaling QA and extracting intelligence from conversations. Observe.AI is frequently discussed as a broader contact-center-focused suite, while Voiceops presents itself as focused on structured data extraction and workflow automation from conversations.
- Voiceops vs CallMiner
  - CallMiner emphasizes established enterprise deployments and clearer guidance on pricing structures tied to users or interaction volume; Voiceops’ pricing is less transparent publicly.
Feature comparison: areas of comparative strength and uncertainty
- Potential Voiceops strengths (vendor-stated)
  - Dynamic schema updates as new signals are identified.
  - Focus on pushing structured outputs into operational workflows (CRM fields, alerts).
- Potential gaps / unknowns
  - Public documentation about enterprise governance features (RBAC, audit logs, data retention) is limited.
  - Multi-channel parity (chat/email/SMS) versus voice-first capabilities should be validated in pilots.
Pricing comparison: value proposition vs alternatives
- Most enterprise conversation intelligence tools are sales-led and require commitments; ROI validation via pilots and reference checks is recommended.
Customer testimonials comparing this product to competitors
- No independent customer comparisons were located in the accessible sources.
Market share and adoption trends
- No quantitative market share data for Voiceops was found in the sources reviewed. The vendor lists customer logos on some pages; these are not a substitute for quantified adoption metrics.

	Voiceops	Observe.AI	CallMiner
Starting Price	Sales-led, custom pricing (no public tiers)	Sales-led, custom pricing (no public tiers)	Sales-led bundled pricing based on users or interaction volume
Best Fit	Mid-market/enterprise B2C teams seeking structured conversation data and workflow outputs for QA, compliance, and operational automation	Contact centers seeking an integrated suite with agent assistance, QA, real-time coaching, and analytics	Mid-to-large contact centers focused on enterprise-grade conversation analytics and VoC programs
Key Strength	Vendor emphasizes dynamic schema updates, creation of custom extractors, multilingual support, and workflow outputs into operational systems	Broad platform depth in contact center AI, including real-time assist and agent workflows	Established enterprise deployments with pricing approaches tied to volume or users; strong analytics focus
Key Weakness	Limited independent review footprint; publicly available security/compliance documentation is limited; pricing is not transparent	Also sales-led pricing and may require larger minimum commitments depending on scope	Can be heavyweight to implement for smaller teams; pricing is typically sales-led