We build production LLM systems.
Not chatbots.
Structured extraction, classification, decision support — schema-validated, observable, and boring on purpose. We also ship lending platforms, WhatsApp portals, and n8n automations for teams that want fewer demos and more shipped software.
Four things. Done seriously.
We don't dabble. Every engagement falls into one of these four pillars — and the depth shows.
AI-Powered Software Development
Production LLM systems for classification, extraction, and decision support — not chat windows. Schema-validated outputs with Pydantic, Anthropic Claude, MCP, FastAPI, and n8n.
- →Lead qualification: warm / lukewarm / cold from long-form content
- →Document extraction with audit trails
- →Decision-support workflows with human-in-the-loop
Custom Software for Lending & Financial Services
Onboarding, KYC routing, credit decisioning, and disbursement tracking. State-machine workflows, PostgreSQL, n8n orchestration — built by people who've shipped fintech.
- →Multi-bureau credit dashboards (CIBIL / CRIF / Equifax)
- →KYC + document collection pipelines
- →Disbursement and collections tracking
WhatsApp Business API Integration & Portal
Multi-tenant WABA portals via Meta Embedded Signup — from app review to template approval. We handle the Graph API mess so your customers don't see it.
- →Embedded Signup + OAuth / System User tokens
- →Template approval, phone verification, webhooks
- →Next.js + Express portal infrastructure
Business Process Automation with n8n
Self-hosted n8n automations that replace manual coordination. Scoped in a week, shipped in two, supported on a monthly retainer.
- →Cross-system orchestration (CRM, sheets, email, WhatsApp)
- →Internal tools without admin panels
- →Observable, recoverable, auditable
Proof, not pitch decks.
Client names are anonymized because we ship for serious clients. The technical depth is the credibility.
Lead qualification for a B2B SaaS
Schema-validated warm / lukewarm / cold classification from long-form prospect content, with structured reasoning fields and audit logs.
Multi-bureau credit dashboards for a lending startup
Unified CIBIL, CRIF, and Equifax responses (consumer + commercial) into branded dashboards with derived utilization, tenure, and DPD insights.
Multi-tenant WhatsApp portal for an agency
Embedded Signup, template lifecycle, and broadcast infrastructure serving dozens of merchant tenants — no per-message BSP markup.
Ops automation for a financial services firm
n8n flows replaced manual onboarding coordination, document-chasing spreadsheets, and Slack-handoff Excel files — without a custom admin panel.
Four opinions we don't apologize for.
We have a clear point of view about how to build software that survives contact with reality. If these resonate, we'll probably get along.
We ship the smallest stack that survives production.
Most teams reach for Kubernetes, microservices, and an event bus before they have product-market fit. We pick PostgreSQL, a single deployable, and n8n until it actually breaks — then we change one thing at a time.
Schemas are non-negotiable, especially with LLMs.
An LLM that returns free-form text is a bug surface. We make Pydantic schemas the contract, validate every output, and route validation failures to humans. If your AI feature can't be unit tested, it isn't a feature yet.
We don't build admin panels. We use n8n.
Internal CRUD tools are where engineering time goes to die. n8n gives us forms, scheduled runs, and integrations for free — and your ops team can read the flow. Build admin panels only when you've outgrown n8n, not before.
No retainers without a scoped win first.
Every relationship starts with a 1-2 week shipped deliverable. If we can't show value in two weeks, a 12-month retainer won't fix it. After that, monthly support is a yes.
A small, deliberate toolkit.
Boring technologies, picked because they survive production. No resume-driven engineering.
AI & Data
Backend
Frontend
Automation & Integrations
Infra
Opinions we'll defend.
Short, technical, and unafraid to disagree with the consensus.
Why most LLM apps fail in production (and how to make yours boring)
Free-form LLM output is a runtime bug surface, not a product. Here's why we treat Pydantic schemas as the contract, validate every call, and route failures to humans.
Why we build with n8n instead of writing admin panels
Most internal tools are forms wired to databases — exactly what n8n already is. Here's what we use n8n for, and the line where it stops being the right answer.
Chat is the worst UI for an LLM
Chat windows dump cognitive load on the user and reliability burden on the model. The highest-leverage LLM applications are pipelines, not conversations.
Have a scoped problem?
Let's pick the smallest thing that ships.
We respond within one business day. If we're not the right fit, we'll say so.