Key takeaways
- Highest SWE-Lancer benchmark score (72%) — outperforms OpenAI and Anthropic on production-grade tasks
- Enterprise-first deployment: fully air-gapped, VPC, or on-premise with SOC 2, ISO 27001 compliance
- Small team (5 people) with unicorn exits — powered by proprietary Genie 2 and Lumen models
FAQ
What is Genie by Cosine?
Genie is an autonomous AI software engineer that can handle bug fixes, features, and refactors in parallel, with enterprise-grade security options.
How does Genie compare to other AI coding agents?
Genie achieves 72% on SWE-Lancer, the highest production-grade benchmark score, outperforming both OpenAI and Anthropic models.
Can Genie run on-premise?
Yes, Cosine offers fully air-gapped deployment, VPC deployment, or on-premise installation with no external dependencies.
What security certifications does Cosine have?
SOC 2 attested, ISO 27001 aligned, with support for FINRA, HIPAA, ITAR, and GDPR compliance requirements.
Executive Summary
Genie is Cosine's fully autonomous AI software engineer, achieving the highest score (72%) on the SWE-Lancer benchmark for production-grade coding tasks.[1] Built by a five-person team with unicorn exits, Cosine focuses exclusively on enterprise deployment with air-gapped, VPC, and on-premise options. Their proprietary Genie 2 model powers the agent, with Lumen available for maximum accuracy in VPC deployments.
| Attribute | Value |
|---|---|
| Company | Cosine |
| Founded | ~2023 |
| Funding | Undisclosed |
| Employees | 5 |
| Headquarters | London, UK |
Product Overview
Genie is positioned as an autonomous "software engineering colleague" that works independently on bug fixes, features, and refactors.[1] Unlike tools requiring developer supervision, Genie handles tasks end-to-end: it drafts PRs, you review and merge.
Cosine describes itself as a "Human Reasoning Lab" — they study how humans perform tasks, then teach AI to replicate and exceed that performance.[2]
Key Capabilities
| Capability | Description |
|---|---|
| Parallel Task Execution | Launch multiple tasks simultaneously |
| Integration | GitHub, Jira, Slack connectivity |
| PR Drafting | Automatically creates pull requests for review |
| Multi-Agent | Genie Multi-agent architecture for complex tasks |
| Air-Gapped Deployment | Full on-premise with no external dependencies |
Deployment Options
| Option | Description |
|---|---|
| Fully Air-Gapped | On-premise, no data egress, fine-tunable on internal codebases |
| VPC Deployment | Runs in your cloud behind your firewall |
| Cloud | Standard SaaS option (less emphasized) |
Technical Architecture
Cosine offers multiple deployment architectures to meet different enterprise security requirements:[1]
Air-Gapped Deployment
- Fully installed on customer infrastructure
- No external dependencies or data egress
- Option to fine-tune on internal codebases, frameworks, or languages (including COBOL, Fortran)
- Post-train any open-source model optimized by Cosine's ML research lab
VPC Deployment
- Runs entirely in customer's cloud
- Access to Lumen, Cosine's frontier coding model
- Secure, private deployment behind customer firewall
Key Technical Details
| Aspect | Detail |
|---|---|
| Deployment | Air-gapped, VPC, or Cloud |
| Models | Genie 2 (proprietary), Lumen (frontier model) |
| Integrations | GitHub, Jira, Slack |
| Open Source | No |
Strengths
- Benchmark leadership — 72% on SWE-Lancer, outperforming OpenAI and Anthropic[3]
- Enterprise security — Air-gapped deployment, SOC 2, ISO 27001, supports FINRA/HIPAA/ITAR/GDPR
- Legacy system support — Can fine-tune on COBOL, Fortran, and proprietary languages
- Zero data retention — Customer IP stays with customer, no training on shared models
- Experienced team — Founders with multiple unicorn exits[2]
- Full visibility — Audit logs, fine-grained access controls, IdP integration
Cautions
- Undisclosed funding — Financial stability unclear; small team (5 people) is a risk
- Enterprise-only focus — Not suitable for individual developers or small teams
- Limited public information — Pricing, customer list, and technical details not publicly available
- New entrant — Less track record compared to established players like Cognition (Devin)
- Benchmark-focused marketing — Real-world performance may differ from benchmarks
Pricing & Licensing
Pricing is not publicly available. Enterprise-focused with custom quotes based on deployment model and scale.
Expected cost: Likely $500+/seat/month based on competitive positioning vs. Devin.
Licensing model: Commercial, enterprise contracts
Competitive Positioning
Direct Competitors
| Competitor | Differentiation |
|---|---|
| Devin (Cognition) | Both autonomous engineers; Cosine emphasizes air-gapped deployment and benchmark scores |
| Factory | Both enterprise-focused; Cosine has proprietary models, Factory uses third-party |
| Tembo | Tembo orchestrates multiple agents; Genie is a single autonomous agent |
When to Choose Genie Over Alternatives
- Choose Genie when: You need air-gapped deployment, have strict security/compliance requirements, or work with legacy codebases
- Choose Devin when: You want the established market leader with proven enterprise deployments
- Choose Tembo when: You need agent orchestration across multiple tools rather than a single autonomous agent
Ideal Customer Profile
Best fit:
- Enterprise companies with strict security requirements (financial services, defense, healthcare)
- Organizations needing fully air-gapped AI deployment
- Teams with legacy codebases (COBOL, Fortran, proprietary languages)
- Companies requiring SOC 2, ISO 27001, or regulatory compliance
Poor fit:
- Individual developers or small teams
- Organizations comfortable with cloud-only solutions
- Budget-constrained teams seeking transparent pricing
- Startups needing quick, lightweight solutions
Viability Assessment
| Factor | Assessment |
|---|---|
| Financial Health | Unclear — Undisclosed funding, very small team |
| Market Position | Niche leader — Best benchmark scores, air-gapped focus |
| Innovation Pace | Active — Proprietary Genie 2 and Lumen models |
| Community/Ecosystem | Limited — Enterprise-only, no open source presence |
| Long-term Outlook | Promising if funding secured — Strong technical differentiation |
Cosine's small team is both a strength (focused, experienced) and a risk (limited capacity, no disclosed runway).
Bottom Line
Genie represents the enterprise-grade end of autonomous AI software engineers. With the highest SWE-Lancer benchmark score and unique air-gapped deployment options, it's positioned for organizations where security and compliance trump cost transparency.
Recommended for: Enterprise organizations with strict security requirements, legacy codebases, or regulatory compliance needs.
Not recommended for: Individual developers, small teams, or organizations needing transparent pricing and broad community support.
Outlook: If Cosine secures additional funding and scales the team, they could become the go-to choice for high-security enterprise deployments. The benchmark leadership provides credibility, but the small team is a key risk.
Research by Ry Walker Research • methodology