AI Agents
Agents scoped to one workflow, integrated with your systems, always reviewable by a person.
Solutions
The work between the systems.
Every company runs on a set of undocumented manual bridges: an export from one system, a spreadsheet, a check, an import into another. They are invisible on any org chart and they consume an enormous amount of time. We find them, model them properly, and automate them with the checks kept in place.
The business problem
The cost is hidden because it is distributed. No single person spends all day copying data, but eleven people spend forty minutes each, every day, and the total is a full-time role nobody budgeted for. It is also where most operational errors originate, because manual transcription between systems is exactly the task humans are worst at.
- Data is exported from one system and re-entered into another daily.
- A spreadsheet sits between two systems and has become load-bearing.
- Approvals move by email, so status is whatever the last message said.
- One person knows how the process really works, and they are on holiday.
Before and after
How it runs today
- Someone remembers, or is reminded, that the task is due.
- They export data, open a spreadsheet, and apply rules from memory.
- They email someone for approval and wait, sometimes days.
- They enter the result into the second system by hand.
- Nobody can reconstruct afterwards what was decided or why.
How it runs afterwards
- The workflow triggers on an event or a schedule, with no one remembering.
- Data moves through a validated adapter, and bad records are quarantined rather than silently dropped.
- Rules that were in someone's head are written down and testable.
- Approvals are requested in the tool people already use, with a deadline and a reminder.
- Every run leaves an audit trail showing what happened and who approved it.
How RAIS approaches it
Map before automating
We document how the process actually runs, not how the policy says it runs. The two are almost never the same, and automating the official version breaks things.
Keep the checks, remove the typing
Human checkpoints exist for a reason. We keep the judgement and remove the transcription — that is where the time actually goes.
Fail loudly
An automation that fails silently is worse than the manual process it replaced. Every workflow has explicit error handling, retries and alerting to a named owner.
One process at a time
We finish and hand over one workflow before starting the next. Parallel automation programmes are how organisations end up with six half-built integrations.
Services involved
SaaS Products
From product architecture and MVP to a multi-tenant platform you can actually operate.
Related use cases
Document Processing
Extract structured records from invoices, contracts and forms, with a review threshold before anything is written.
Legacy Workflow Modernization
Replace the load-bearing spreadsheet without stopping the work that depends on it.
API Integration & Orchestration
Connect systems properly — with validation, retries, idempotency and an audit trail.
CRM & Sales Automation
Keep the CRM accurate without asking salespeople to become data entry clerks.
Typical integrations
ERP
Orders, inventory and finance records synchronised through a validated adapter rather than a nightly spreadsheet.
1C
Exchange with 1C configurations through supported interfaces, with reconciliation and a quarantine for bad records.
CRM
Read and write deals, contacts and activities so qualified enquiries land where sales already works.
REST API
Documented, versioned and authenticated endpoints — both consuming yours and exposing ours.
Microsoft 365
Identity, mail, calendars and document libraries, with permissions respected rather than bypassed.
Custom Systems
In-house and legacy systems without a public API, reached through a documented adapter agreed with your team.
Frequently asked
Do we need AI for this?
Often not, and we will tell you when. A large share of manual work is deterministic and is better served by a plain, testable integration — cheaper to build, cheaper to run and far easier to reason about. We reserve AI for the genuinely fuzzy steps: unstructured input, classification and extraction.
Our systems have no API. Is that a blocker?
Usually not, but it changes the approach and the cost. Options include database-level integration, file exchange on a schedule, or a documented adapter. What we avoid where possible is UI automation, which is brittle and breaks on the vendor's next update.
How do you decide what to automate first?
By volume, repetitiveness and cost of error — and, importantly, by whether the process is stable. Automating a process that is about to be redesigned is wasted money, so sometimes the honest recommendation is to wait.
Next solution
Data & Analytics
One version of the numbers, available to the people who have to act on them.
