Document Agents
Understand documents through real language comprehension. Recognition of type, content, and context – not template matching. Every extraction verified through the Decision Layer.
Document Agents in detailAI Agents for enterprises and institutions in Brasilia
On your infrastructure. Under your control.
Brasilia is Brazil’s regulatory and governmental centre. Banco do Brasil, BB Seguridade, Caixa Economica Federal - and ANPD (National Data Protection Authority), the LGPD regulator. For enterprises and institutions headquartered in Brasilia, data and AI regulation is not abstract - it is local. PL 2338/2023 will define additional transparency and human oversight requirements for AI systems. The public and financial sectors in Brasilia operate under particularly stringent audit requirements, with TCU (Federal Court of Accounts) demanding complete traceability. From our Sao Paulo office, we manage projects in Brasilia with on-site presence as needed.
Why do most AI projects fail?
Not because of technology – but because of missing governance. Without clear rules defining who makes which decision, every AI agent stays a pilot project.
That is why we build every agent exclusively with a Decision Layer. It breaks down every business process into individual decision steps and defines for each step: human, rule engine, or AI. No agent goes into production without this layer.
Three agent types for your department
Workflow Agents
Steer business processes across multiple systems and decision points. One agent, complete orchestration. Every step in the audit trail.
HR AI AgentsKnowledge Agents
Answer questions from enterprise knowledge – with source reference, rule version, and validity date. No verified source, no answer.
Knowledge Agents in detailGovernance by Design
Auditable. Compliant. Enterprise-grade.
Human-in-the-Loop architecturally enforced – not optional
Complete audit trail for every agent decision
GDPR compliant by design – all data on your infrastructure
Works council compatible – agreements as constraints in the Decision Layer
EU AI Act compliant by design – transparency, explainability, human oversight
Model-agnostic – no vendor lock-in, you own the source code
From PoC to platform
1
Discover
1 week
Process analysis, understand rule sets, prioritise use cases.
2
Build
3–4 weeks
Productive PoC. One agent, one process, live on your infrastructure.
3
Scale
Continuous
More agents, more processes. Same governance, same auditability.
After 12–18 months, you operate your agents independently. Source code, prompts, and rule sets are yours.
Go deeper
Analysis and insights on enterprise AI, governance, and agent architecture.
HR & People Operations
Why AI Projects in HR Fail
Most AI projects fail not because of technology but because nobody defined the rules. Why the operating model matters more than the language model.
Governance & Compliance
EU AI Act: What HR Departments Must Do Now
The EU AI Act directly affects HR processes. Risk classification, bias monitoring, human oversight - what is now mandatory and how to prepare.
HR & People Operations
Why HR Departments Need to Build Agent Governance Now
Agent governance is not an IT topic. It's an HR leadership topic. What CHROs need to know before AI agents enter core HR processes.
“Even as a global market leader, you want to keep moving forward. It is reassuring to have the technological expertise and infrastructure experience of Gosign on our side.”
Head of Innovation, Sony Music Entertainment
“Gosign is not just about speed. It's about how much essential work happens in this time.”
Head of Customer Service & Technical Support, Libri GmbH
Frequently Asked Questions
Does Gosign serve the public sector in Brasilia?
Yes. Our governance architecture - complete Audit Trail, Decision Layer with Human-in-the-Loop, Cert-Ready by Design - meets the requirements of regulated environments, including the public sector.
What role does ANPD play for my enterprise?
ANPD (National Data Protection Authority), headquartered in Brasilia, supervises LGPD compliance. PL 2338/2023 will add transparency and human oversight requirements for AI - which our agents implement by design.
How do the agents meet TCU audit requirements?
Complete Audit Trail: every agent decision produces a record with input, model, assessment, confidence score, rationale, decision path, and result. Immutable, exportable, audit-ready.
How quickly is a first AI agent productive?
4-6 weeks. Discovery: 1 week. Build: 3-4 weeks. On your infrastructure.
Which process should your first agent handle?
Talk to us about a specific use case in your organisation.
Book a meeting