Agentic Index

Cosine vs Poolside (2026)

This is the sovereign AI engineering matchup. Both deliver coding agents inside your security perimeter for regulated and defense grade buyers. Cosine is lighter and self serve, from 20 dollars a seat, with Genie plus Lumen models and air gapped options. Poolside is the heavyweight: full model weights delivered to your environment, a governed agent console, and IL5 deployability, sold enterprise only through embedded engineers.

At a glance Cosine Poolside
Category Coding agent Coding agent
Entry price Hobby $20/seat/mo (5M credits) · Professional $200/seat/mo (60M credits) · credits per task; top-ups available · BYO Claude/OpenAI/Copilot uses your own subscription · enterprise air-gapped custom Enterprise pricing is custom and not public, deployed in your environment through Forward Deployed Research Engineers. Poolside models are also available usage based in Amazon Bedrock. The Laguna XS.2 open weight model is free under Apache 2.0.
Free / trial No free tier surfaced; entry is the $20/seat Hobby plan. Note: running Genie on your own Claude/OpenAI/Copilot subscription via the CLI incurs no extra Cosine model billing. No public self serve trial of the enterprise platform; access starts with a sales conversation. A free path exists through the open weight Laguna XS.2 model, which runs locally under an Apache license, and through Amazon Bedrock usage based access.
Pricing confidence public exact contact only
Feature
C
Cosine
Action & orchestration

Integrations & Tool Calling

Ability to connect agents to real systems through native integrations, OAuth-authenticated actions, custom tools, APIs, webhooks, or MCP-compatible tools.

Full / Explicit Full / Explicit

Workflow Orchestration

Ability to sequence, branch, retry, route, and combine deterministic workflow nodes with autonomous agent steps.

Full / Explicit Full / Explicit

Triggers & Channel Coverage

How agents wake up and where they work: schedules, webhooks, message events, CRM events, inbox events, chat, email, voice, and collaboration tools.

Full / Explicit Partial
Knowledge & context

Knowledge Grounding & RAG

Ability to ground agent behavior in company data through document ingestion, retrieval, external knowledge APIs, semantic search, or RAG layers.

Full / Explicit Full / Explicit

Memory & State Persistence

Ability to persist context across a run, conversation, workflow, user, team, or longer-term memory layer.

No / Not documented No / Not documented
Control & trust

Human Oversight & Guardrails

Approval steps, consent checkpoints, escalation rules, structured guardrails, policy constraints, and pause/resume controls.

Partial Full / Explicit

Security, Identity & Governance

RBAC, SSO, auditability, encryption, least-privilege tool access, compliance posture, and data handling policy.

Partial Full / Explicit

Observability & Auditability

Traces, logs, execution histories, metrics, audit events, and debugging detail for production agent behavior.

Partial Full / Explicit

Deployment & Data Residency

Deployment modes and options, including SaaS, dedicated cloud, VPC, on-prem, hybrid, local runtime, and self-hosting.

Full / Explicit Full / Explicit
Solution readiness

Prebuilt Agents, Templates & Packs

Ready-made workflows, packaged employees, templates, blueprints, industry solutions, and role-specific agents that reduce time-to-value.

No / Not documented Partial
Platform extensibility

Model Flexibility & Routing

Ability to work across multiple foundation models, route tasks to different models, or let buyers bring their own providers and keys.

Full / Explicit Full / Explicit

APIs, SDKs & MCP Extensibility

Composability layer: stable APIs, SDKs, MCP tool consumption/serving, custom tools, and integration into internal systems.

Partial Partial

Testing, Debugging & Optimization

Testing, debugging, scoring, retries, fallbacks, quality gates, and optimization loops for improving agent workflows before and after deployment.

Partial Partial
Specialist automation

Browser & Computer Use

Browser, desktop, or remote/local computer control for workflows that cannot be handled through stable APIs alone.

Partial Partial

Pricing snapshot

Sourced from the Index pricing dataset · open each vendor's profile for full detail.

Pricing
C
Cosine

Entry price

Lowest public entry point

Hobby $20/seat/mo (5M credits) · Professional $200/seat/mo (60M credits) · credits per task; top-ups available · BYO Claude/OpenAI/Copilot uses your own subscription · enterprise air-gapped custom Enterprise pricing is custom and not public, deployed in your environment through Forward Deployed Research Engineers. Poolside models are also available usage based in Amazon Bedrock. The Laguna XS.2 open weight model is free under Apache 2.0.

Pricing confidence

How public the numbers are

Public — exact Contact only

Billing

Primary billing axis

Seat-based subscription with a monthly Cosine Credit pool per seat (credits consumed when the agent reads, plans, or writes code); additional seats add users and credits; top-ups available; enterprise/air-gapped via custom agreements. BYO model subscription path bills model usage to your own provider. Enterprise deployment is a custom contract sized to the environment and developer count, delivered with Forward Deployed Research Engineers. Poolside models are also available usage based in Amazon Bedrock, priced per token. The Laguna XS.2 model is free to run locally under an Apache license.

Variable cost

Workload / overage exposure

High variable cost Medium variable cost

Free tier / trial

Try before you buy

No free tier
Free tier

Buying motion

Self-serve vs sales call

Self-serve Sales call

Choose Cosine if

  • You want sovereign capability without an enterprise procurement cycle; plans start at 20 dollars a seat.
  • Legacy language coverage through Lumen is directly relevant to your codebase.
  • Running the agent on your existing model subscriptions fits your current spend.

Choose Poolside if

  • You require full weight delivery and air gapped operation up to government grade, including IL5.
  • Fine tuning foundation models on your own code and docs is part of the plan.
  • Forward deployed engineers embedding with your team suits your adoption model.

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