Solutions · AI & Automation
AI that reasons over your data, with a person in the loop.
Grounded AI assistants, intelligent agents, document intelligence and workflow automation, designed to be reliable in real operations, not just impressive in a demo.
01 · The problem
Most operations still run on copy-paste.
Reports exported by hand, data re-keyed between systems, templated emails, approval chains chased over chat. A well-designed automation does this work reliably. A badly designed one fails quietly.
We start by mapping the actual workflow, then design the automation, including error handling, retries and escalation to a person, before anything is built. For AI steps, we ground answers in your verified knowledge base and send low-confidence outputs to human review rather than passing them through.
- Solution
- AI & Automation
- Core stack
- Python
- FastAPI
- LLM integration
- n8n
- PostgreSQL
- Docker
- Engagement
- Project delivery · Ongoing development · Technical advisory
- Location
- Engineering team in Chennai. We work with clients remotely across India and beyond.
02 · Capabilities
What we build.
Retrieval-augmented AI
Assistants and search that answer from your own documents and data, not from guesswork.
Intelligent agents
Multi-step agents that act across your systems within clearly defined permissions.
Workflow automation
Event-driven pipelines connecting CRM, ERP, communication and reporting tools, including with n8n.
Document intelligence
Extraction from PDFs, invoices and forms, validated against rules before it reaches your systems.
Conversational assistants
Customer-support and internal-helpdesk assistants with escalation paths to your team.
Monitoring & control
Alerts on failure, run history and documentation, so your team can see and fix what runs.
03 · Who it is for
Built for teams where the system carries weight.
- Operations teamsReclaiming time spent on repetitive, rules-based work between systems.
- Financial and trading firmsAutomating reporting, reconciliation and notifications around market systems.
- Education providersAutomating enrolment, communication, certification and support workflows.
04 · How we work
The same five phases, on every engagement.
Architecture comes before code, and validation comes before launch. You can see what is being built at every stage. Our approach
Discover
Stakeholder interviews, workflow mapping and a technical review of existing systems, so we understand the real problem before proposing anything.
Architect
System architecture, data models and API contracts, documented and agreed before the full build starts.
Build
Iterative delivery in short cycles, with regular demonstrations, code review and continuous integration.
Validate
Functional, integration and failure-mode testing. For critical systems, a parallel run before cut-over.
Operate
Deployment, monitoring, documentation and handover, with ongoing support and improvement where needed.
05 · Related work
Related work and products.
06 · Technology
Chosen for the problem.
We work with a small core stack we know deeply, and we select technology to fit each platform's requirements rather than trends. See our technology.
- Python
- FastAPI
- LLM integration
- n8n
- PostgreSQL
- Docker
07 · FAQ
Questions, answered plainly.
How do you stop AI from making things up?
By design. Answers are grounded in a verified knowledge base through retrieval-augmented generation, outputs are checked against rules where possible, and anything below a confidence threshold goes to a person.
Can automation run on our own infrastructure?
Yes. Workflows and AI components can be deployed on your cloud account or on-premise, so sensitive data stays in your environment.
Do you work with systems that have no API?
Often, yes: through database-level integration, file-based exchange or a lightweight API built around the existing system. We assess feasibility during discovery.