AI strategy & advisory
Opportunity mapping, feasibility studies and roadmaps that separate what AI can do for you today from what is still hype.
Research & development · AI + Blockchain
We research, prove and build intelligent systems for real industries.
alba.one is an applied R&D company. We help organisations work out where AI and blockchain genuinely fit, prove it with working prototypes, and then engineer the production systems — shaped around the rules, data and people of their industry.
- AI + Web3 One team fluent in both stacks
- Vertical-first Built around your sector's rules and data
- Lab to launch From research question to running system
What we do
From research question to production system
Engage us for a focused advisory sprint, a funded R&D programme, or an end-to-end build. See all services →
Applied AI & machine learning
Predictive models, computer vision, document intelligence and LLM agents, evaluated against your data before they ship.
Blockchain & digital assets
Traceability ledgers, tokenisation, verifiable credentials and smart contracts, where a shared record actually earns its cost.
Research & prototyping
Time-boxed experiments and proofs of concept with clear success criteria, so you can decide with evidence.
Data engineering
Pipelines, data products and governance: the unglamorous foundation every intelligent system stands on.
Integration & scale
Production engineering, MLOps, security reviews and hand-over, so the prototype becomes something your team can run.
Industries
Built for the sector, not the demo
Generic tools rarely survive contact with a regulated, multi-party industry. We start from the domain. Explore industries →
Agriculture & food
Crop and yield intelligence, farm-to-fork traceability and farmer credit scoring from alternative data.
Financial services
Fraud and risk models, KYC automation, tokenised assets and programmable payments on mobile-money rails.
Health
Clinical document AI, supply-chain integrity for medicines and consent-aware health records.
Logistics & trade
Demand forecasting, route optimisation and shared, tamper-evident trade documents across borders.
Energy & climate
Grid and asset forecasting, and measurable, verifiable carbon and renewable-energy credits.
Public sector
Digital identity, land and registry systems, and citizen-service assistants that respect privacy.
Where AI meets the ledger
Intelligence you can trust, records you can verify
AI makes decisions faster. Blockchain makes them accountable. Much of our work sits where the two meet.
- Discipline Applied R&D
- Stacks AI · Blockchain · Data
- Outcome Auditable automation
A model scores a loan, grades a harvest or flags a shipment. We anchor a fingerprint of that decision — the inputs, model version and output — to a ledger. Regulators, partners and customers can later confirm exactly what was decided and when, without anyone exposing the underlying data.
python# Anchor an AI decision to a public ledger
import hashlib, json
from web3 import Web3
w3 = Web3(Web3.HTTPProvider(RPC_URL))
registry = w3.eth.contract(address=REGISTRY, abi=ABI)
def anchor(decision: dict) -> str:
"""Hash inputs, model version and output; store only the hash."""
payload = json.dumps(decision, sort_keys=True).encode()
digest = hashlib.sha256(payload).digest()
tx = registry.functions.anchor(digest).transact({"from": OPERATOR})
receipt = w3.eth.wait_for_transaction_receipt(tx)
return receipt.transactionHash.hex()
anchor({
"model": "credit-score@2.4.1",
"input_ref": "app_8c21f",
"score": 0.82,
"decided_at": "2026-09-01T10:14:00Z",
})
How we work
Explore, prove, build, scale
Four phases with clear exits. You decide whether to continue at the end of each one, with evidence in hand.
Explore
Map the problem, the data and the constraints. Leave with a ranked set of opportunities and a plan.
Prove
Build a working prototype against real data, measured on success criteria agreed up front.
Build
Engineer the production system: integrations, security, monitoring and user experience.
Scale
Operate, retrain, extend to new markets and transfer the know-how to your team.
Insights
Notes from the lab
What we are learning while building. All insights →
When does a blockchain actually make sense?
A five-question test we run before recommending a distributed ledger — and why the honest answer is often "not yet".
Read article →Designing AI for low-bandwidth markets
Why assuming a fast, constant connection quietly breaks AI products in the field, and the patterns we use instead.
Read article →From proof of concept to production without the pilot purgatory
Most innovation pilots never reach production. Four habits that make it far more likely that yours will.
Read article →Have a problem worth researching?
Tell us the goal, the constraints and the deadline. We reply with a plan within two working days.