Operational workflows that run themselves.
Custom multi-agent systems that compress cycle times across document processing, approvals, integrations, and decision workflows — built compliance-native with full IP ownership.
Six capability areas. One engineering team.
From document intake to ERP write-back — we build the full workflow, not isolated components.
Multi-Agent Workflows
Autonomous agent pipelines that decompose complex processes, route decisions, and complete tasks with minimal human intervention.
Intelligent Document Processing (IDP)
Extract, classify, validate, and route structured data from unstructured documents — invoices, contracts, forms, and reports.
ERP & System Integrations
Connect AI workflows to your ERP, CRM, HRMS, or proprietary systems via API or RPA. No manual data re-entry.
Approval & Escalation Automation
Rules-based and AI-driven approval workflows with audit trails, escalation paths, and SLA monitoring.
Process Telemetry
Instrument your workflows with observability — cycle time measurement, bottleneck detection, exception tracking, and executive reporting.
AI Governance Layer
Every automation is built with ISO 42001-aligned guardrails — logging, explainability, human override paths, and model card documentation.
Audit first. Build second. Deploy with accountability.
Every engagement follows the same disciplined process — from process mapping through production monitoring.
Process audit
We map your current process, identify automation opportunities, and quantify time and cost savings before building anything. No spec without evidence.
Architecture and compliance review
We design the automation architecture and run it through an ISO 42001-aligned risk review before development starts. Regulated-industry deployments get additional scrutiny.
Build, test, and validate
Agents are built iteratively with your team. Every workflow is tested against edge cases, exception paths, and human-in-the-loop scenarios before production.
Deploy and monitor
Production deployment with telemetry, alerting, and a named Golonex engineer responsible for ongoing performance and model drift.
Built for regulated environments.
AI automation in financial services, healthcare, and government-adjacent industries requires more than a working model — it requires accountability at every layer.
- ✓ Full audit trail on every AI decision — who triggered it, what model, what output.
- ✓ Human override paths built into every workflow — not bolted on after.
- ✓ ISO 42001-aligned model documentation delivered as a project artefact, not an afterthought.
Frequently asked questions
Who owns the IP once the automation is built? +
You do — entirely. All agents, workflows, models, training data, and documentation produced during the engagement are transferred to you at project close. Golonex retains no rights to anything built. You can deploy it, modify it, or hand it to another team without restriction. This is in the contract, not just in the pitch.
How do you handle sensitive data during development? +
Development uses anonymised or synthetic data wherever possible. Where production data must be used for fine-tuning or testing, it stays in your environment or an agreed secure workspace — it is never sent to public model APIs or processed outside the agreed data boundary. We produce a data handling record as a project artefact.
Is this suitable for regulated industries like banking or healthcare? +
Yes — and we are structured for it. Regulated deployments include an ISO 42001-aligned governance layer: a model card, a use policy, a risk assessment, and an audit trail. For banking clients, we design around RBI data residency requirements and ensure no personal financial data transits unapproved infrastructure.
What business systems have you integrated with? +
SAP, Oracle NetSuite, Microsoft Dynamics 365, Salesforce, Tally (common across Indian businesses), and multiple proprietary core banking platforms. Integration is via API where available, RPA where it is not, and native connectors for M365 and Google Workspace. If your system is not listed, share the API documentation and we will confirm feasibility before scoping begins.
Does the automation need maintenance after delivery? +
Most automations benefit from periodic model review — inputs drift over time and workflows need revalidation as underlying systems change. We offer an optional maintenance retainer covering quarterly health checks, prompt tuning, and workflow adjustments. You can also maintain it in-house if your team has the capability; we produce documentation sufficient for that handoff.
Tell us what process needs to be automated
Share the workflow — volume, current steps, systems involved. We will map the automation opportunity and respond within one business day.