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.
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
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.
- In place in weeks.
A senior team starts on the first workflow 2–4 weeks after signature.
- Kept by the company.
Code, models, prompts and tests run in its own cloud, free to take in-house.
- Free to switch models.
Each task uses whichever model passes its test at the lowest cost.
- Measured in business terms.
Every workflow reports against the number agreed with leadership.
Strategy already set and a partner needed to build it?
Ways to work together
Three ways to bring Twistag into a plan that is already set.
Dedicated squad
A senior team inside the programme.
Best forHeads of engineering or innovation with an approved roadmap and too few senior people to deliver it on time.
- Engineering, data and product lead
- Works in the client’s tools and rituals
- Sized up or down each quarter
Fixed-scope build
One system, delivered to spec.
Best forProgramme leads with a clear spec, a budget and a deadline, who need one system built and handed over.
- Fixed price and delivery date
- Acceptance tests agreed up front
- Code and models handed over in full
Loop subscription
AI engineering on a monthly plan.
Best forProduct and tech teams with a steady queue of smaller AI builds and no case for a full-time hire.
- One monthly fee
- Requests turned around in days
- Pause or stop at any time
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 in production
Delivery & ProcessCut process complexity before you add 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.
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.
