One install, four environments
The same Howlet runs on a developer's laptop, in an offline factory, and on AWS. You don't relearn the product when the environment changes.
From GenAI Studio to compliance, from stream processing to source control, all in the same codebase, same authorization, same audit. Architectural decisions are published as ADRs by our product team.
Every headline below is a real mechanism your engineers can inspect on the product page.
The same Howlet runs on a developer's laptop, in an offline factory, and on AWS. You don't relearn the product when the environment changes.
A natural-language command connects to your own code repo and builds AI and data flows in Howlet Studio 50-100× faster. Your source code never leaves; critical actions require human approval, and every step lands in a tamper-evident audit trail.
When a subject requests erasure, the data is removed in cascade across seven separate systems. The 30-day window is monitored live, and a signed evidence pack is produced for the regulator.
Deploy to AWS Istanbul Local Zone and keep all data within Turkish borders. KVKK data residency is satisfied at the infrastructure level, not through contractual workarounds.
Replace 6–8 vendors in your AI/ML stack with a single platform; clear your integration backlog.
Build production-grade AI agents. Each agent runs isolated, with three layers of safety filtering on input, output and execution.
Send a natural-language command and the Howlet Coding Agent builds AI and data flows 50-100x faster. Your source code never leaves; every step lands in a tamper-evident audit trail.
Open your enterprise documents to AI safely. 11 connectors, four vector backends and Turkish-aware PII detection out of the box.
Design ETL and transformation flows visually. Howlet picks the right engine: fast on small data, Spark at scale. You never choose the engine manually.
Train models, run hyperparameter sweeps, measure fairness. GPU quotas, idle shutdown and audit logging are built into every step.
Register models, promote across three environments, choose canary, shadow or A/B. When drift is detected, retraining is triggered automatically.
Kafka, Flink, Spark or NiFi. Howlet picks the engine that fits your topology, not the other way around. All designed in one canvas.
Your visual artifacts sync with Git automatically. A single atomic commit pushes 30 files to any of four major Git providers.
Trace a user request from sign-in to LLM call in one window. A log line, a distributed trace and an AI invocation share the same correlation ID.
Day-one operations for erasure requests, consent management and policy enforcement. The file you'd hand a regulator is one click away.
Let employees sign in with their existing corporate identity; when permissions change, they don't need to log in again. SSO and MFA are standard.
Four authority tiers: root, platform, tenant, workspace. Idle GPUs scale to zero; backups run continuously without disrupting users.
Each tier sees and audits only its own scope. If the root account is lost, the runbook offers a three-step recovery path; there is no dead end.
Always-on MFA, IP allow-list and sudo TTL enforced. Recovery in three layers: codes, CLI, manual DB. Hardcoded role exclusion from Remember Me.
Tenant lifecycle, profile upgrades, GPU quotas, audit access. Sees every tenant's perimeter; cannot cross into one.
Manages workspaces, users and licenses. Database-per-tenant isolation enforced; no path into other tenants' data.
Projects, RBAC assignment and environment promotions for a single team. Sees only that team's audit trail.
When a subject requests erasure, Howlet cleans every system the data passed through. The 30-day statutory window is tracked live and a signed evidence pack is produced automatically.
Training to serving, RAG to streaming, RBAC to disaster recovery. Not vendor lock-in. Installed on your own infrastructure.
On-prem · air-gapped · AWS. Your data stays with you, the proof stays in the chain.