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Lightfield
AI-native CRM that builds itself from your conversations.
What it does
• Auto-captures contacts, accounts, and opportunities directly from incoming emails, calendars, and live meetings. • Extracts action items and commitments automatically to draft personalized customer follow-up emails. • Processes natural language queries to answer complex pipeline questions with direct citations to original conversation moments. • Synchronizes versioned customer memory across the entire organization to power autonomous outbound sales agents.
Why it works
Eliminates administrative CRM data entry friction, ensuring pipeline records stay accurate without manual updates. Versioned customer memory preserves deep context across all historical touchpoints rather than flat data fields. Natural language querying allows instant access to specific conversation insights with exact call citations. Autonomous agent workflows proactively scale outbound lead generation and routine follow-up communications.
Category: AI & Automation
Team Size: 11-25
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As of 2026
AI & Automation
Revenue: $1M-$10M ARR
AI-native CRM that builds itself from your conversations.
Overview
Lightfield is an AI-native customer relationship management platform that automatically builds a living model of every account using data extracted from emails, meetings, and calls. It eliminates manual data entry by capturing customer signals, tracking commitments, and drafting contextual follow-ups in the background. Users can query past interactions in plain English to uncover deep pipeline insights with verifiable citations. The system provides high-growth sales teams with automated pipeline generation and unified customer memory.
Funding status: Funded
Revenue source: Subscriptions
Customer type: B2B
Pricing: Subscription
Tech stack: Cloud Infrastructure, Advanced LLMs, Vector Database, Agent SDK
Platform: Web
Integrations: Google Calendar, Gmail, Outlook, Slack, REST APIs, Model Context Protocol (MCP)
Founder story
Lightfield was founded in 2020 by Keith Peiris, Henri L., and Pete Nichols. Drawing from their experience building high-scale consumer and productivity products, the founders set out to replace rigid legacy CRMs with an AI-native system that learns directly from real customer conversations.
What it does
- • Auto-captures contacts, accounts, and opportunities directly from incoming emails, calendars, and live meetings
- • Extracts action items and commitments automatically to draft personalized customer follow-up emails
- • Processes natural language queries to answer complex pipeline questions with direct citations to original conversation moments
- • Synchronizes versioned customer memory across the entire organization to power autonomous outbound sales agents.
Who it's for
- Startup Founders
- Sales Teams
- Account Executives
- Growth Leaders
Why it works
- Eliminates administrative CRM data entry friction, ensuring pipeline records stay accurate without manual updates
- Versioned customer memory preserves deep context across all historical touchpoints rather than flat data fields
- Natural language querying allows instant access to specific conversation insights with exact call citations
- Autonomous agent workflows proactively scale outbound lead generation and routine follow-up communications.
Growth strategies
- Targeting startup founders and modern sales teams frustrated by legacy CRM data entry bloat
- Product- led growth through viral word-of-mouth and high-engagement community launches
- Providing frictionless calendar and inbox integrations for rapid five- minute onboarding
- Continuous rollout of advanced workflow automations, Slack agents, and custom object capabilities
Alternatives
Comparison overview
- [Operates as an AI-native CRM that automatically populates records from calls and emails rather than expecting manual field entry , Provides deep conversation querying with direct source citations instead of relying solely on static database fields , Focuses on maintaining a continuous versioned memory of relationship changes rather than simple status stages]