How much does Nektar.ai cost?

Not published for the plans. nektar.ai/pricing lists Bloom and Harvest, billed per user per month and priced on request with volume discounts, and one published add-on, Data Backfill at $8 per user for every month of data backfilled.

What are the best alternatives to Nektar.ai?

Based on documented capability coverage across the Agentic Index 14 point taxonomy, the closest alternatives to Nektar.ai among GTM and revenue agents are BambooBox, Sybill, Tofu, Aircover.ai. Each is graded on the same public evidence, and no vendor pays for placement.

Does Nektar.ai have SOC 2, SSO and role based access control?

Partial under the Agentic Index verification standard. Nektar.ai publishes some public evidence of security and identity controls, but narrower than the full set of SOC 2, single sign on (SSO) and role based access control (RBAC). Evidence basis: SOC 2, ISO 27001 and CASA Tier 2 certification is stated, a trust portal is linked, and Nektar offers granular privacy controls and data masking over what is captured. No customer-facing access model, such as SSO, roles or user permissions. Graded from public evidence only against the Agentic Index 14 point capability taxonomy. No vendor pays for placement.

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Nektar.ai

Q: Who is Nektar.ai for?

Enterprise revenue and RevOps teams, GTM and sales organizations, Teams building agentic GTM systems

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GTM / revenue agentindependentVerified 2026-10-01

Entry priceNot published; Bloom and Harvest plans per user, on requestFull pricing detail

GTM telemetry that captures every customer interaction and writes it into the CRM and warehouse automatically, plus DAISY, an AI agent for buying-group, deal-health and forecast intelligence.

Nektar is a GTM telemetry platform that positions itself as the trusted customer context layer for revenue AI. Its Revenue Telemetry layer automatically captures every customer email, meeting, calendar event and contact across the lifecycle, matches each to the right account and opportunity with a proprietary entity-matching engine, and writes it into Salesforce, HubSpot or Dynamics with no rep involvement, creating contacts, opportunity contact roles and field updates along the way. A self-healing Time Travel feature retroactively corrects records as new context arrives and backfills history, and data syncs bi-directionally with Snowflake and into the customer's internal AI models.

On top of that foundation, DAISY is Nektar's AI agent for revenue intelligence: buying-group detection, deal-health and churn-risk signals, forecast intelligence and engagement insights for RevOps, marketing operations, customer success and sales teams. Nektar states SOC 2, ISO 27001 and CASA Tier 2 certification, offers granular privacy controls and data masking, and runs as a hosted service that writes into the customer's own systems.

Vendor details

Canonical URL

https://nektar.ai

Funding status

Headquartered in Singapore with US operations. Customers named on the vendor's pages include Brex, Mimecast, Cursor, Writer, Chainguard, Ironclad, Alteryx and Docusign.

Company status

independent

Use cases & customers

Primary use cases

Automated CRM activity capture and enrichmentGTM data foundation for AI agentsBuying committee and opportunity role detectionRevenue intelligence and pipeline data hygiene

Target customers

Enterprise revenue and RevOps teamsGTM and sales organizationsTeams building agentic GTM systems

Deployment options

SaaSCustomer data warehouse delivery (Snowflake)

Integrations

Bi-directional integration with Salesforce and Snowflake, capturing from Gmail, Microsoft, Zoom, and Slack, enriching with third party and signature data, and piping structured intelligence into CRM, data warehouse, and AI apps like Claude, with no browser extension or rep sidebar.

Sources & related URLs

Research sources

https://nektar.ai/ https://nektar.ai/llms.txt https://nektar.ai/generative-ai/

Agentic Index coverage score

4.5 / 14 capabilities · 32%

Integrations & Tool Calling	Full
Native integrations with Salesforce, HubSpot and Dynamics write captured activity, new contacts, opportunity contact roles and field updates into the CRM automatically, alongside bi-directional Snowflake integration and capture from email, calendar, meeting and Gong sources. Those are native, OAuth-authenticated read-write actions in real systems. SourceNektar, nektar.ai homepage and llms.txtread 2026-09-21
Workflow Orchestration	Partial
A capture, match, correct and write pipeline runs end to end inside Nektar, with its entity-matching engine and self-healing Time Travel correction deciding where each activity lands, and customers configure what is captured. That is a fixed pipeline the vendor runs, with no orchestration surface exposed. SourceNektar, nektar.ai homepage and llms.txtread 2026-09-21
Knowledge Grounding & RAG	Full
The content of every customer email, meeting and contact across the lifecycle is captured, matched to the right account and opportunity and retroactively corrected as new context arrives, and Nektar grounds its DAISY revenue intelligence on that record while delivering it to Salesforce, Snowflake and the customer's internal AI models. That record is maintained and continuously refreshed, persists, and stays usable by agents. SourceNektar, nektar.ai/generative-ai and homepageread 2026-09-21
Human Oversight & Guardrails	Not documented
By design, Nektar captures and writes activity with no rep involvement, and no approval step, escalation rule or pause for a person's sign-off before its automation or agent acts is documented. SourceNektar, nektar.ai homepageread 2026-09-21
Security, Identity & Governance	Partial
SOC 2, ISO 27001 and CASA Tier 2 certification is stated, a trust portal is linked, and Nektar offers granular privacy controls and data masking over what is captured. No customer-facing access model, such as SSO, roles or user permissions over who in the customer's organization can do what, is documented. SourceNektar, nektar.ai homepage and llms.txtread 2026-09-21
Observability & Auditability	Not documented
Reporting covers engagement, meeting coverage and pipeline signals from the customer's sales activity, and the records Nektar's automation writes land in the customer's own CRM, which supplies their history. No run level record of what Nektar's automation or its DAISY agent did, step by step, is documented. SourceNektar, nektar.ai homepage and llms.txtread 2026-09-21
Memory & State Persistence	Not documented
Nektar's historical and real-time interaction record is written into the customer's CRM and warehouse as standard and custom fields, so deleting it would delete the business record: that is the application's data model, not a memory layer, and no memory with a stated scope and lifetime that an agent reads across sessions is documented. SourceNektar, nektar.ai homepageread 2026-09-21
Deployment & Data Residency	Not documented
As a hosted service, Nektar writes its output into the customer's CRM and data warehouse; no self-hosted, private cloud or region selection option for Nektar itself is published. SourceNektar, nektar.ai homepage and llms.txtread 2026-09-21
Prebuilt Agents / Templates / Packs	Partial
DAISY, Nektar's AI agent, bundles buying-group detection, deal-health signals, forecast intelligence, churn risk and engagement insights, and role pages present solutions for RevOps, marketing operations, customer success and sales. These are functions of one agent and marketing for roles rather than a set of separately adoptable agents or templates. SourceNektar, nektar.ai llms.txt and homepageread 2026-09-21
Triggers & Channel Coverage	Full
Every email, meeting and calendar event across the customer's accounts starts Nektar's capture, matching and CRM write with no rep involvement, and new context retroactively triggers corrections through Time Travel, so work reaches the automation from events without a person initiating it. SourceNektar, nektar.ai homepageread 2026-09-21
Model Flexibility & Routing	Not documented
Activity matching and classification, and DAISY itself, run on Nektar's own AI and machine learning, and no model choice, provider selection or bring-your-own-key option is documented. SourceNektar, nektar.ai homepage and llms.txtread 2026-09-21
APIs / SDKs / MCP Extensibility	Not documented
Structured data flows from Nektar into the customer's CRM, Snowflake and internal AI models, but no API, SDK or MCP server for calling Nektar's own platform is documented. SourceNektar, nektar.ai llms.txt, homepage and generative-airead 2026-09-21
Testing, Debugging & Optimization	Not documented
Nektar states a matching accuracy figure for its own entity-resolution engine, which is the vendor's measurement of its product, and no evaluation harness, scored test cases or quality gate for a customer's agent is documented. SourceNektar, nektar.ai homepageread 2026-09-21
Browser / Computer-use	Not documented
Nektar captures activity server-side from email, calendar and meeting systems with no browser plugin, and no browser, desktop or computer control by an agent is documented. SourceNektar, nektar.ai homepageread 2026-09-21

The Agentic Index coverage score grades every vendor Full, Partial or Not documented against the same 14 buyer facing capabilities, from public evidence only. Each capability links to how all vendors in the index score on it. How this evidence is graded

Recent platform changes

2026-08-10·IntegrationsVerified

Nektar introduced a native integration with Gong that automatically captures meeting metadata, attendee information, and full conversation transcripts. The integration synchronizes this conversation data directly into Nektar's engagement layer alongside existing email, calendar, and CRM activity.

Bears on: Memory / state

View source

View all 1 change for Nektar.ai →Tracked since Aug 2026 · Verified from public vendor sources

Pricing

Not published; Bloom and Harvest plans per user, on request

per user per month by plan; data backfill add-on

What is public

Plan names, what each includes, per user billing and the $8 Data Backfill add-on.

Cost watchouts

Data Backfill is charged at $8 per user for every month backfilled, on top of the plan.

Variable cost rationale

Reviewers describe per user style licensing that scales as seats are added, plus data volume captured and warehouse delivery; exact rates were not retrieved this session.

Sales call required

Yes, required for paid access

Free / trial

No published trial; request pricing or a demo

Key ambiguities

Bloom and Harvest are priced on request; only the Data Backfill add-on carries a published figure.

Missing data

Bloom and Harvest per user prices; volume discount terms.

Agentic Index verified 2026-10-01

Official pricing page

Related vendors

Alternatives to Nektar.ai

The closest documented capability profiles to Nektar.ai among GTM and revenue agents tracked by Agentic Index, ordered by similarity on the same 14 point evidence the rankings use. No vendor pays for placement.

BambooBox5.5 / 14Adds documented Memory & State Persistence
Sybill6.5 / 14Adds documented Human Oversight & Guardrails and Observability & Auditability, among others
Tofu5.5 / 14Adds documented Human Oversight & Guardrails and Memory & State Persistence
Aircover.ai7.0 / 14Adds documented Memory & State Persistence and APIs, SDKs & MCP Extensibility
AnyBiz4.0 / 14Adds documented Memory & State Persistence and Browser & Computer Use
FlashLabs5.0 / 14Adds documented Memory & State Persistence

Similarity is computed from each vendor's Agentic Index coverage score evidence, axis by axis, not from the totals. How this evidence is graded

Compare Nektar.ai with other vendors →Compare all GTM and revenue agents →See where Nektar.ai ranks →

Data confidence: medium

Head to head

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