Custom AI agents
Autonomous support, sales and operations agents that read, decide and act across your tools - with guardrails, retries, and a human in the loop on anything high-stakes. Not a chatbot bolted to an FAQ.
AI Development Company
We're an AI development company that ships to production.
Solvornx designs and builds the entire AI layer of your business - custom AI agents, LLM and RAG systems, automation pipelines and AI-powered products. Engineered with the evals, guardrails and observability that keep them working under real traffic, not just in a demo.
17+ products shippedBuilding since 2019Evals on every build
Agent · running
In plain English
AI that survives
contact with reality.
Almost anyone can wire an API to a chat box and call it AI. The hard part - the part that decides whether AI actually helps your business - is everything around the model: retrieval over your real data, guardrails, evaluation, fallbacks, and the integration work that lets it act inside the tools your team already uses.
As an AI development company, that's the part we own. We start by finding the workflow where automation pays off, ship the smallest reliable system that moves the number, and grow it from there - with a human in the loop wherever the cost of a mistake is real.
Model-agnostic. Frontier or open models, whatever fits the job and budget. No lock-in.
Grounded, not guessing. Retrieval and citations over your data, so answers are traceable.
Measured, not vibes. An evaluation harness scores quality before anything ships.
What we build
The full AI stack.
One team across agents, LLMs, retrieval and the MLOps that holds it all together - so there are no gaps between a clever prototype and a system in production.
LLM development & fine-tuning
Large language model applications tuned to your domain, data and tone. We pick (or fine-tune) the right model, prompt and structure it properly, and measure it against a real evaluation set instead of guesswork.
RAG & knowledge systems
Retrieval-augmented generation grounded in your documents, policies and databases - with citations, access controls and freshness guarantees so answers are accurate and traceable, not confidently wrong.
AI automation & pipelines
Document processing, data entry, enrichment, routing and reporting run unattended. The repetitive work your team does by hand, handled 24/7 with full observability.
AI-powered products
Copilots, semantic search, generation and recommendation built into the core of a product - engineered as a real feature with the reliability paying customers expect.
Evals, guardrails & MLOps
Evaluation harnesses, drift monitoring, fallbacks and dashboards. The unglamorous layer that turns a clever demo into a system you can actually trust in production.
Built for production
Demo-grade AI breaks.
Ours holds.
The difference between AI that wows in a demo and AI you can trust on real traffic is everything around the model. This is that everything - and it's in every system we ship.
Evaluation harness
A test suite scores every change before it ships, so quality is measured - not hoped for.
Human-in-the-loop
Anything high-stakes pauses for a person to approve. The agent knows what it shouldn't decide alone.
Fallbacks & retries
When a step fails it retries, then routes to a human. It never silently drops work.
Full observability
Every action is logged and visible on a dashboard. You always know what's running and why.
Where teams use it
Put to work.
The AI we build earns its place by removing real, repetitive work. A few of the jobs we've automated and the ones we're asked for most.
- Customer support agents that resolve tickets, not deflect them
- Document processing & intelligent data extraction at scale
- Sales & outbound automation with human approval gates
- Internal copilots over your own docs and data (RAG)
- Lead scoring, routing and CRM enrichment
- Back-office automation: reconciliation, reporting, ops
Selected AI work
AI we've shipped.
Two AI products we took from idea to production. More across web, mobile and SaaS in our selected work.
AI document processing at enterprise scale
We engineered an intelligent document-processing engine for DataFabricX and redesigned the platform UI from the ground up - accurate extraction across messy, real-world documents for their enterprise clients.
500k+Documents processed
90%Data accuracy
A 24/7 AI digital identity for creators
An always-on AI identity trained on a professional's voice, knowledge and brand - AI chat, AI voice, smart profiles, lead capture and scheduling unified into one experience that represents them around the clock.
10 minTo launch a profile
24/7Always answering
How we work
Workflow to production.
Every AI build follows the same honest rhythm - find what matters, architect it properly, then ship it with the evals that keep it trustworthy.
Find where AI actually pays off
Two weeks with your team. We map the workflows, score them by leverage and feasibility, and define what 'good' looks like - measurably - before any model is chosen.
Duration · 1-2 weeksDesign the system, not just the prompt
Model choice, retrieval, guardrails, eval plan, data flow and fallbacks - documented and signed off before we build. The failure paths are designed as carefully as the happy path.
Duration · 1 weekBuild it production-grade
Agent logic, retrieval, integrations and an evaluation harness, built in tight iterations and demoed weekly. Quality is tracked against a test set from the first commit.
Duration · 4-8 weeksShip, watch, improve
Deployed with observability, drift detection and human-in-the-loop checkpoints. We tune it on real usage and hand over clean docs - you own all of it.
Duration · OngoingThe stack
Tools we reach for.
We're not married to one provider or framework. We pick what fits the problem and your budget - and write code your team owns.
PythonTypeScriptOpenAIAnthropicLangGraphVector DBsRAGFine-tuningEvalsAWS / GCPObservability
Questions
The AI development
questions.
What does an AI development company actually deliver?
A working AI system in production - agents, an LLM feature, or a RAG pipeline - plus the evals, monitoring, and documentation to run it. Not a demo, and not a slide deck.
Which AI models do you use?
Whatever fits the job and budget - frontier models where quality demands it, smaller or open models where they're enough. You're never locked to one provider.
Can it use our private data safely?
Yes. It reads your documents and systems through retrieval with access controls and citations, so answers are grounded and traceable - and sensitive data stays where it belongs.
How long does an AI build take?
A focused agent or RAG system is usually 4-8 weeks to production; a full AI-powered product is longer. You get a fixed scope and timeline after the free audit.
Do we own the model and the code?
Always. Everything ships to your repositories and accounts - no vendor lock-in, no licensing games.
Got an AI idea worth shipping?
We'll find the highest-leverage thing to build first - free, in a two-week audit. You keep the plan either way.