Finance
Invoices that match themselves.
An agent reads every supplier invoice, in any format, and matches it to orders and receipts in the ERP. The finance team sees only the exceptions.
2,000+invoices a month for Aralab
NewThe AI-Native Playbook for Enterprises
Rebuilding companies into AI‑native businesses
Twistag is an applied AI company. We design, build and run the agents and data systems that take on real operational work. Based in Lisbon, working with companies in Portugal and worldwide.
What changes for the business
AI-native companies do more with the team they have.
Twistag works with leadership to rebuild how work gets done. Agents take the volume, people keep the judgement, and the business grows without headcount growing at the same pace.
The AI-native advantage
- Margins that hold as volume grows
- Decisions made on today's numbers
- Teams focused on customers and judgement
- Capacity added in weeks
- Systems the company owns outright
Twistag designs, builds and runs it alongside leadership, one proven workflow at a time.
Since 2016
A decade of systems companies run on every day.
Partner
Most of what a company spends goes on work that moves between people and systems: reading, checking, matching, chasing. AI can now carry much of that work. Making it hold up inside a real business, with real data and real accountability, is what we do.
How we workWhere it shows up
Where the work changes first.
Operations
Staffing planned against real demand.
Occupancy forecasts move people between nearby sites before outside agencies are called. Managers approve the plan; the agent does the arithmetic.
70%less agency staffing spend for a European hotel group
Customer service
Replies drafted in the company's own voice.
Every message is classified, the account pulled up and a reply drafted against house guidelines. A person approves it in one click.
Everydraft checked for a UK water utility
Compliance
Every launch checked, market by market.
Ingredient and label rules are applied country by country, with each finding tied to the regulation behind it, before a product ships.
75%less diligence effort for a European RegTech
Practices
One team, from the data up.
AI projects stall in the gaps between vendors. We cover the full path, so nothing waits on a handoff.
01
Agents that plan, decide and act across company workflows, with people approving what matters and every decision traced.
- Agentic workflows
- Multi-agent systems
- Search over company knowledge
- Human review steps
02
Data platforms agents can actually read: clean, current and connected to the ERP and CRM, on infrastructure the business controls.
- Data platforms and pipelines
- Data lakes and warehouses
- Data governance
- ERP and CRM integration
03
AI-native products and internal tools, and the platforms around them, designed, shipped and run by the same team.
- Web and mobile products
- Internal tools and portals
- API design
- Legacy modernisation
Find the work closest to the challenge.
Answer two questions to see the most relevant project, service and reading.
1. IndustryQuestion 1 of 2
2. Business needQuestion 2 of 2
Selected as the industry and as the business need.
Recommended
Ready to move ahead
Skip the reading and talk it through.
A 30-minute call with a senior Twistag lead on the workflow, the data and what a first proof could look like.
Approach
Commitment grows only after proof.
The first two steps are small and fixed in time. Scale starts once the number agreed with leadership has moved.
- 01 · 2 weeks
Find the workflow
Map where work waits, what fixing it is worth and which number will prove it, with the people who run the process.
- 02 · 6–8 weeks
Prove it
One workflow rebuilt around agents on real data, and tested against that number before anything scales.
- 03 · Quarters
Scale it
Each new workflow builds on the same foundation, so every one ships faster than the last.
- 04 · Ongoing
Run and hand over
Improved from real use, then handed over. Code, models and tests stay in the company’s own cloud.
Start here
Not sure where to start?
The AI Readiness Check: fifteen questions across five areas, a score and the first fixes in two minutes.
Take a 2min AI Readiness Check →Plan already set
Strategy already set?
Three ways to bring Twistag in: a fixed-scope project, forward deployed engineers, or a partnership.
Ways to work together
Three ways to bring Twistag into a plan that is already set.
Prove it
Fixed-scope
project
Best forCompanies with a clear problem, a budget and a date: one system, built to spec and handed over.
- Fixed price and launch date, agreed before the start
- Acceptance tests written with the team up front
- Code, models and documentation handed over in full
Scale it
Forward Deployed
Engineering
Best forAn approved roadmap that needs senior engineers who think like operators, inside the company’s own teams.
- One to three senior engineers, each with agents
- Side by side with the operators
- In the company’s infrastructure, tools and rituals
With partners
Partners and
portfolios
Best forCompanies that build AI, data and product with Twistag: tech companies, consulting and PE firms.
- Senior capacity for a tech company’s own roadmap
- Tech delivery for consulting firm’s clients
- AI playbooks rolled out across PE portcos
Industries
Built for the companies that keep things running.
Choose a sector to talk to the team that works in it.
Thinking
Our thoughts on AI, data and product.
Short, practical reading on putting AI to work, from the team doing it every day. All thinking
Featured · Playbook · Web and PDF
The AI-Native Playbook for Enterprises
How leadership teams choose the first workflows, prove the value and scale AI across the business. Written from Twistag engagements.
Five engineering reasons AI agents fail once live
Delivery & ProcessCut process complexity before adding AI agents
AI & AgentsHow long does it take to ship an AI agent to production?
Newsletter
One email a month on what is working with AI inside real companies.
Questions
Before the first call.
How quickly do results show up?
A team is in place two to four weeks after signature. The first system runs on real data within six to eight weeks, measured against the number agreed at the start.
What does an engagement cost?
The proof phase is scoped and priced up front, so the risk is known before work starts. What follows is priced against the rollout plan agreed with leadership. A company can also start with the two-minute AI Readiness Check.
Who owns the code, the models and the data?
The client owns all code and IP. Data stays in the client's own cloud, and the work follows ISO 27001 practice.
What if the proof doesn't move the number?
Then nothing scales. The company keeps the code, the findings and a clear view of what would need to change.
Will our own team be able to run it?
Yes. Every engagement ends with documentation, evaluations, runbooks and time working alongside the client's engineers.
Talk to us
Bring AI into the work of every team.
A conversation on where agents add capacity, what it takes to build them, and which number shows it is working.
A senior lead replies within one working day.
