Everyone has access to the same AI. So why do only some companies get results?
The model is the same for everybody. What changes the result is what comes before and after it: your data organized, rules for who can do what, a record of every decision, and all of it running inside your own house. That is what the Catech Platform delivers.
KYC Verifier
productionowner @risk · golden-path kyc-v2
Run trace
live · run #4192- fetch documents
- extract entities
- screen against sanctionsrunning
- risk decision
Audit trail
immutable · RBAC- @ana.riskapproved run2m
- systemwritten to immutable log2m
- @rilo.engdeployed kyc-v21h
From your data to the work delivered.
Your data, where it already lives
Data layer · PostgreSQL · Snowflake · Databricks · S3
We connect your databases and files without moving anything. Organization is automatic; the data stays in your house.
The context of your business
Semantic layer · Knowledge bases · Context
The AI learns how your company works and answers about it, not about the internet.
The work getting done
Agent execution · Memory · Execution trace
Agents do real work: they use your systems, remember what they have done and leave a trace of every step.
The rule and the record
Governance · Immutable logs · Granular RBAC · SOC 2-ready
Who can do what, with a history nobody can erase. Every read, write and approval is logged.
Where all of it lives
Deployment · On-premises · Private VPC · Air-gapped
Your cloud, your server, or fully cut off from the internet. Your data never crosses the company border.
Your team is in charge.
It runs in your cloud, in your datacenter, or fully cut off from the internet. None of your data becomes training for someone else's model. Every access goes through a rule your team defined, and every read, write and approval lands in a history nobody erases, not even us. Our engineers set it up alongside your team. After that, the keys are yours.
- Each person sees and does only what their role allows, and it is logged
- GDPR and LGPD from the foundation, not as a patch
- Architecture prepared for SOC 2 Type II certification
- In your cloud, on your server, or off the internet: your call
If you are on the technical side, this is where the conversation gets specific.
Data sources
PostgreSQL, Snowflake, Databricks, SAP, Salesforce, Oracle and proprietary systems via API.
Model engine
Agnostic orchestration: OpenAI, Anthropic, DeepSeek or local models via vLLM.
Monitoring
Logs, traces and metrics exported to the dashboards you already use: Datadog, Grafana or your SIEM.
A technical session with the people who built it.
Discuss architecture, security and on-premises deployment directly with the people who built the platform.
Request engineering contact