AI coding tools, configured to your standards, from day one.
Your engineers move faster. Your compliance team sleeps better. Your AI investment finally delivers.
The compliance control plane for regulated engineering teams.
Your team adopted AI coding tools. Your codebase didn't notice.
AI tool usage is up 65% across the industry, but median PR throughput has only grown 7.8%. A few power users get leverage; everyone else gets inconsistent results. Every coding session starts from zero because context lives in Slack threads and people's heads. And the most transformative capability, autonomous agents, stays on the shelf because no regulated org can safely deploy them. The adoption gap isn't a tooling problem. It's a standards and context problem.
The adoption gap, and what it costs
Even at the 90th percentile
Top-performing teams still leave more than half the productivity on the table
DX, 2026Free AI Compliance Assessment ยท First scan in 48 hours
Three problems, one platform
Different companies. Different stacks. The same three problems.
[anthara] solves all three, so your AI adoption actually delivers.
What You Get
How [anthara] sits in your stack
Standards flow into your engineers' tools. Every prompt and tool call flows out through governance. All of it stays inside your network.
Policy Layer
Compliance Packs
Versioned packs for HIPAA, PCI-DSS, WCAG, SOC 2, and your internal standards, enforced at the moment code is generated. Not after the PR.
Memory Layer
Org-Wide Context
Org-wide knowledge and codebase context, injected into every AI session automatically. Adaptive, not static buckets. Your engineers teach it once, every tool remembers.
Gateway
Outbound Proxy
Fine-grained controls for MCP tool governance, plus PHI and PII masking and guardrails. Every prompt and tool call is policy-checked before it leaves your network.
Agents
Custom Automation
Multi-step agents triggered on events, governed by everything else in [anthara]. Read tickets, generate plans, write code, raise PRs. The autonomous-agent dream, made deployable in a regulated environment.
Under the Hood
From first scan to automated workflows in four steps
Who It's For
Built for regulated engineering teams adopting AI
Healthtech. Fintech. Any team where AI-generated code must meet standards before it ships.
VP of Engineering
"The board wants 2-3x productivity from AI. Compliance wants proof we won't get fined. I need to deliver both, fast."
[anthara] makes your AI adoption actually deliver. Standards enforced at generation means fewer rework cycles, cleaner PRs, and faster merges, while giving your CISO an audit trail that proves governance. Productivity and compliance stop being a tradeoff.
Staff / Senior Engineers
"I want every prompt hardened, every tool following our standards, and work product that's not just fast but safe."
[anthara] gives your AI tools organizational memory: architecture decisions, coding standards, and compliance rules injected automatically. Every agent on your team writes code the way your team writes code.
Compliance & Security
"People keep asking about AI governance and nobody has answers. I need evidence, not promises."
[anthara] gives you audit trails, regulatory boundary enforcement across HIPAA, PCI-DSS, WCAG, and SOC 2, and provable compliance posture. Updated daily as regulations evolve. You'll have answers before anyone asks the questions.
Common Questions
What teams ask before getting started
Do I need to give [anthara] access to my source code?
[anthara] can run on-premises or in your VPC (BYOM). Code, PHI, and PCI data never leave your security boundary. The initial assessment requires read access to your repos. Nothing is stored after the report is generated.
Which AI coding tools does [anthara] work with?
Claude Code, Cursor, GitHub Copilot, Codex, and Cline. Guardrails are delivered as standard rule files (.cursorrules, CLAUDE.md, copilot instructions) and organizational memory is delivered via the Model Context Protocol (MCP).
How long does it take to get started?
You receive your first AI Compliance Assessment within 48 hours. No code changes or integrations required. Policy pack deployment and organizational memory setup typically take days, not months.
What are governed AI workflows?
YAML-defined processes that read tickets from Jira, generate implementation plans, write code, and raise pull requests, all running inside your compliance policy packs. Every agent tool call is policy-checked and logged. Engineers review and approve with one click; the AI executes under governance.
How is this different from a code scanning tool?
Scanners find problems after code is written. [anthara] prevents them. Policy packs and MCP governance ensure AI tools generate compliant code and take compliant actions from the start. Scanners still have a role; [anthara] sits upstream of them and reduces the work they have to do.
How is this different from an AI gateway like Kong?
AI gateways govern AI traffic, any application talking to any LLM. [anthara] governs AI-assisted engineering specifically. The policy packs, MCP tool governance, and organizational memory are built for how engineers write code with AI, with regulated-industry standards built in. A regulated company will typically need both, serving different problems.
How is this different from a GRC platform like Vanta?
GRC platforms handle the paperwork side of compliance: evidence collection, vendor risk, attestation. [anthara] handles the runtime side, enforcing compliance at the moment AI-generated code is produced. Different category, different budget, complementary.
What does it cost?
The AI Compliance Assessment is free. [anthara] is priced as compliance infrastructure, a platform fee with per-repo or per-seat terms, not as a per-developer productivity SKU. Reach out to discuss pricing based on your team size and deployment model.
Measurably better AI-generated code.
From day one.
See where your team stands, before you commit to anything.
Get Your Free AssessmentNo integration required. First report in 48 hours.