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Agentic AI & RAG Systems

Autonomous Agents
Grounded In
Your Own Data.

Multi-step AI agents that plan, decide, and act across your tools — plus RAG systems that give them accurate, grounded knowledge of your business.

Start Your Project See capabilities
24/7
Autonomous agents
0
Hallucinated answers
4wk
Avg. to production
RAG LLM API RAG Agents Vector DB Tool Use
What we do

AI that knows your business — and acts on it.

General-purpose chatbots don't know your products, your policies, or your data — so they guess. RAG (retrieval-augmented generation) fixes that by grounding every answer in your actual content, with citations and no hallucination.

Agentic systems go a step further: multi-step agents that plan, call tools and APIs, and complete real tasks autonomously — research, data processing, outreach, and operations — running 24/7 without human handholding.

Grounded, never guessing. RAG retrieves from your data so answers are accurate and cited.
Agents that take action. Not just chat — agents call tools and complete multi-step tasks.
Self-improving knowledge. Knowledge bases that expand automatically as gaps are found.
RAG Knowledge Systems
Grounded answers from your data
Autonomous Agents
Plan, decide, and act on tools
Vector Search
Semantic retrieval at scale
Tool & API Use
Agents that do real work
Capabilities

What our agents & RAG do.

Every capability is production-ready from day one — not a demo, not an experiment. Built to scale.

RAG Knowledge Systems
Ground AI answers in your documents, catalog, and policies — with citations.
  • Vector embeddings
  • Semantic retrieval
  • Source citations
Autonomous Agents
Multi-step agents that plan and act across tools and APIs.
  • Planning & reasoning
  • Tool / API calling
  • Multi-step tasks
Vector Search
Fast, semantic search over large private knowledge bases.
  • Pinecone / Weaviate
  • Metadata filtering
  • Hybrid search
Document Ingestion
Pipelines that chunk, embed, and index any content automatically.
  • Any format ingestion
  • Auto re-indexing
  • Access control
Tool-Using Agents
Agents that call your systems to complete real work, not just chat.
  • Function calling
  • CRM / API actions
  • Human-in-the-loop
Continuous Improvement
Knowledge bases that learn and expand from unanswered questions.
  • Gap detection
  • Auto-expansion
  • Eval & monitoring
Business challenges

Knowledge problems we solve.

The most common bottlenecks holding businesses back — and exactly how we eliminate them.

⚠ The problem
Chatbots that hallucinate — Generic AI invents answers it can't back up — a liability, not an asset.
Knowledge trapped in docs — Answers exist somewhere in your files, but nobody can find them fast.
Manual multi-step work — Research, data gathering, and routing done by hand, step by step.
AI that can't take action — Assistants that talk but can't actually do anything in your systems.
✦ With Velox
RAG grounds every answer in your real data with citations — accurate, verifiable, no hallucination.
Semantic vector search surfaces the right answer from your knowledge base instantly.
Autonomous agents handle multi-step workflows end-to-end, running 24/7.
Tool-using agents call your APIs and systems to complete real tasks, with human review where it matters.
How we work

Our development process.

The same proven process across every engagement — from a 3-week build to a multi-month platform.

01
Understand requirements
A focused discovery session — we map your current process, the bottleneck, your data, and the measurable outcome we're building toward. We come with questions, not slides.
Free · 30 minProcess mappingSuccess metrics defined
02
Strategy & planning
We design the right architecture for your problem and deliver a fixed-price proposal within 3–5 days, with a week-by-week delivery plan.
3–5 daysArchitecture designFixed price
03
Build & iterate
We build and rigorously test against your success metrics, with weekly live demos so you see real, working progress — not status updates.
Weekly demosWorking softwareEdge-case testing
04
Integration & deployment
We connect the solution to your existing systems and deploy to your environment. Full source-code transfer included.
Your infrastructureFull source codeTeam training
05
Optimisation & support
Post-launch we monitor, refine, and improve based on real usage. Support retainers available for ongoing engineering.
Performance monitoringIterationSupport retainers
Technology

The stack behind the work.

Production-proven tools — not whatever is trending this month.

LangChain
Orchestration
CrewAI
Multi-agent
Pinecone
Vector DB
Weaviate
Vector DB
GPT-4 / Claude
Reasoning LLMs
text-embedding-3
Embeddings
n8n
Agent workflows
Python
Agent stack
Why Velox

What makes our work different.

Not every agency has shipped production systems. We have — and the difference shows in everything we deliver.

Custom-built, not templated
Everything we ship is built for your specific problem and data — not a generic template wrapped in your logo.
Scales without the cost
Architected to handle 10× the volume with zero marginal cost. Growth doesn't require proportional headcount.
Secure & compliant by design
HIPAA, GDPR, and enterprise security built into the architecture — private VPCs, encryption, on-device options.
4–8 weeks to production
We eliminate the 6-month cycle. Fixed scope, weekly demos, production in weeks. Velox is Latin for fast.
Senior engineers, every project
No juniors learning on your production system. Every engagement is staffed by engineers who have shipped real systems.
50+
Systems in production
4–8wk
Average delivery
98%
Client satisfaction
0
Junior engineers on your project
Accelerating Intelligence.
Use cases

Where agents deliver.

Deployed across industries — each with different data and constraints. Same production quality across all of them.

E-commerce
Support assistants grounded in catalog and orders.
RAG
B2B SaaS
Internal knowledge and research agents.
Agents
Healthcare
Clinical and policy knowledge assistants.
Compliant
Legal
Document research and contract analysis.
Cited
Enterprise
Knowledge bases and ops automation agents.
Scale
Related case studies

Agentic systems we've shipped.

All case studies →
E-commerce · RAG Pipeline
RAG Support Automation — D2C Skincare Brand
73% of support tickets were repeat questions, answered slowly.
RAG on catalog + Shopify context + escalation handoff
80%
Auto-resolved
4wk
To production
HR Tech · AI Automation
CV Screening & Ranking Automation
Recruiters spending 60% of their time screening CVs by hand.
Agentic ingestion + LLM scoring + ATS push
85%
Time saved
3wk
To production
SaaS · AI Solutions
AI Lead Intelligence Platform
Inbound leads sitting 2–3 days before first contact.
LLM enrichment + scoring agent + auto outreach
3×
Lead throughput
5wk
To production
FAQ

Common questions.

Anything not answered here — reach out directly.

Ask us anything →
What is RAG, in plain terms?
Retrieval-augmented generation. Instead of the AI guessing, it first retrieves the relevant facts from your data, then answers using only those — with citations. That's how you get accurate, grounded responses.
How do agents differ from a chatbot?
A chatbot talks. An agent acts — it plans a multi-step task, calls tools and APIs, and completes work autonomously, escalating to a human only when needed.
Will it hallucinate?
RAG dramatically reduces hallucination by grounding answers in your data and citing sources. We also add guardrails and evaluation so answers stay trustworthy.
Do we need a huge dataset?
No — RAG works with the documents and data you already have. There's no model training required to get started.
Get started

Ready to Build
Your AI Agent?

Tell us what you want it to know or do — we'll build a grounded, autonomous system around your data.

Start Your Project See our work
Free 30-min discovery call  ·  Fixed pricing  ·  Production in 4–8 weeks