Finora Intelligence
From scattered research to one auditable answer.
An AI research workspace that helps investment teams move from raw documents to client-ready insight in minutes.
- faster research
- 72%
- weekly adoption
- 3.4×
- platform uptime
- 99.9%
AI that earns its keep.
No chatbot theatre. We identify where intelligence creates leverage, prove the value quickly, then deploy a system your team can trust.
- faster research for Finora Intelligence
- 72%
Practical AI systems grounded in your data, workflows, and actual business case.
AI opportunity mapping
RAG and knowledge systems
Agentic workflows
Document intelligence
Forecasting and classification
Model evaluation
Everything needed to make it real.
We shape the engagement around the problem, but the handoff is always complete, documented and built to keep moving.
- Use-case scorecard
- Data readiness review
- Working prototype
- Production AI service
- Evaluation framework
- Monitoring and handover
Typical stack
From useful question to working system.
Week 1 · Discovery
Start with the constraint
The useful brief is rarely “build an app.” We find the bottleneck, the behavior, and the business result first.
Weeks 2–3 · Prototype
Show the work early
Real prototypes beat long decks. You see the product taking shape every week and decisions stay reversible longer.
Build · Weekly releases
Build for Monday morning
A clever demo means nothing if the team cannot operate it. Reliability, clarity, and handover are part of the product.
After launch
Measure the change
The launch is a checkpoint. We track adoption, time saved, conversion, and the next constraint worth removing.
See it working.
All case studiesMost projects cross more than one.
Web development
Fast, distinctive web experiences engineered to turn attention into action.
ExploreWorkflow automation
Connected workflows that remove handoffs, errors, and repetitive operational work.
ExploreMobile apps
Thoughtful mobile products built around everyday behavior, not feature checklists.
Explore
Questions, answered.
Can’t find yours? Ask us directly. We reply within one working day.
Ask a questionWe build retrieval-augmented generation (RAG) knowledge systems, AI agents that complete multi-step tasks, document intelligence that reads and extracts from PDFs and forms, and forecasting or classification models. Each one is grounded in your own data and workflows.
Every system ships with an evaluation framework. We test answers against real examples from your business, link generated answers back to their sources, and monitor quality after launch so problems are caught early.
We work with OpenAI, Anthropic and open-source models, using LangGraph, Pinecone, FastAPI and Python. We choose the model per task on accuracy, cost, speed and data privacy needs.
Most AI projects start with a short discovery sprint that scores use cases and checks your data. A working prototype on real data usually follows within a few weeks, before any larger investment.
Bring us the constraint. We’ll bring the team.
Every applied AI engagement starts with one candid conversation about what’s in the way.