Less busywork. Better workflows.

AI that does the work.
Guardrails that keep you in control.

We start with how your team works, then connect your systems and take repetitive tasks off their plate. We use rules for predictable steps, AI where it helps, and human review for exceptions and consequential decisions. Every solution is tested before rollout, using a sandbox, sample data, or a digital twin where appropriate.

Architect-led, network-deliveredAutomation roots that predate LLMsTested safely before rollout

Figure 01 · How work moves

AI does the reading.
You keep control.

Follow one document from arrival to completion.

InputDocument arrives

Email, PDF or form

AIRead the details

Extract the information

RulesCheck the record

Match records and agreed limits

Within the rulesComplete the task

Update your systems automatically.

Human reviewPause for a decision

A person approves consequential actions.

1 / 4 · Document received

A signed customer agreement arrives in the inbox.

Illustrative workflow · No real records are changed.

Expand detailed animationCollapse detailed animation
The full picture

Existing animation: lookups, checks, approvals and corrections.

Swipe or scroll sideways to explore the full diagram.

INBOX email · PDF · form EXTRACT LLM reads it name · email LOOKUP rules · CRM VALIDATE cross-check guardrail ANALYZE route by risk DONE CRM · ERP routine: record, folders, invite HUMAN sign-off money · commitments · outbound approve decline · needs changes RETURNED TO SENDER with the reason missing fields corrected copy re-enters the inbox FIG. 01 — GUARDRAILED ORCHESTRATION WITH A HUMAN IN THE LOOP blue = automation · orange = guardrail / human
  1. Inbox: receive the email, PDF or form.
  2. Extract and look up: AI reads details; rules match the CRM.
  3. Validate and analyze: cross-check the data and route by risk.
  4. Routine records complete automatically; consequential actions wait for approval.
  5. Missing or declined information returns for correction and checking again.

Blue: automated work · Orange: safeguards and human review

What an AI Automation Architect does

Understand the work. Build the right solution. Test it safely.

Your AI Automation Architect starts with the work your team does every day. We identify what is worth automating, connect the tools you already use, and agree where people need to stay involved.

01 / ASSESS

Find out what is worth automating

Start with one workflow that takes too much time. A full feasibility audit is a separately priced, fixed-scope assessment of the work, the data and the likely benefits.

  • Find the delays. Follow the work with the people who do it and identify where it gets stuck.
  • Choose the right approach. Decide which steps need a simple rule, AI assistance, or a person.
  • Check the information. Find missing, inconsistent or unreliable records before building on them.
RESULTA written verdict per workflow: automate now, fix the data first, or keep it human.
02 / DESIGN

Build systems that do the work

Design the simplest reliable way to move the work forward. Connect your existing software and use AI only where it adds value.

  • Connect the steps. Move information between the tools your team already uses, without repeated copying and pasting.
  • Make the rules clear. Define what can happen automatically and what should stop for review.
  • Keep people in control. Route exceptions and consequential decisions to the right person.
RESULTConnected workflows with agreed rules, and human approval for exceptions and consequential decisions.
03 / TEST

Test it safely before it goes live

Testing matched to the workflow and its risks. Use sample data, sandbox integrations, or a digital twin where appropriate. A twin can model workflows and edge cases, or help explore a business decision before you commit.

  • Use realistic examples. Try representative documents and records in a safe test environment.
  • Check what happens when things go wrong. Test missing information, conflicting records and unusual cases.
  • Explore a business decision. Where useful, model a change in pricing, staffing or suppliers before committing. Try the demonstration.
RESULTDocumented test results, issues to resolve, and agreed conditions for going live.

See a workflow assessment

See where rules, AI and people fit.

Follow this illustrative customer-onboarding workflow. Each step gets a recommendation: use a rule, use AI assistance, or keep a person in charge. This example is not a client result.

The proposed improvement: rules move checked records between systems, AI reads the PDFs and drafts the welcome, and your team still approves the credit terms.

Before, after and how we would measure it

Before: A person reads each agreement, copies details into the CRM, chases missing information and waits for credit approval.

After: AI extracts the details, rules check and transfer the information, and exceptions or consequential decisions wait for a person. Your team reviews the welcome draft.

Measure: Compare time from agreement received to account ready, staff handling time, correction rates and approval turnaround against a baseline from the current process. Agree targets before rollout and check them during the trial.

This is an illustrative proposal, not a client case study or a claim of measured savings.

Rules: predictable stepsAI: reads and draftsPeople: judgment and approval
Example · customer onboarding idle
01Receive signed agreementemail attachmentRules
02Extract client details from the contractnames · terms · addressesAI assistance
03Create the account record in the CRMchecked informationRules
04Approve credit terms above thresholdcredit above the agreed limitHuman approval
05Draft the welcome and kickoff emaildraft for reviewAI assistance
06Schedule kickoff and notify the account ownercalendar · SlackRules
0Automate now
0AI-assisted
0Keep human
EXAMPLE DATA READINESS —

How an engagement runs

Assess. Design. Test. Launch.

Each phase ends in a deliverable you own, whether or not you continue. No black boxes. Scope, deliverables, and price are set before each phase starts.

PHASE 1 · ASSESS

Full feasibility audit · paid

Scope and price are agreed separately after initial discovery. We follow the workflow with your team, check the information it relies on, and identify what is worth automating.

Deliverable: Automation Blueprint with a go / fix-first / no-go verdict
PHASE 2 · DESIGN

System design

Agree how the steps connect, what runs automatically, and which decisions need approval before we build.

Deliverable: Solution design with risks and safeguards
PHASE 3 · TEST

Safe testing

Test with sample data, sandbox integrations, or a digital twin where appropriate. Measure results and check failure cases before rollout.

Deliverable: Documented test results
PHASE 4 · LAUNCH

Go-live and handover

Introduce the workflow in stages, monitor the results, and train your team to run it.

Deliverable: Operating guide and 30-day tuning

Phase 3, up close

Test the workflow before rollout. Use a digital twin when it fits.

Testing is matched to the scope and risk of the work. Where a digital twin is appropriate, it models representative record structures, volumes, and edge cases. Other projects use sample data or sandbox integrations. You receive documented test results and agreed controls for a staged rollout. The same discipline, pointed at a business decision instead of a workflow, is decision simulation →

FIG. 02 — TEST BEFORE ROLLOUT

  1. 1. Use a safe test environment

    Sample data, sandbox integrations, or a digital twin where appropriate.

  2. 2. Try ordinary and difficult cases

    Check missing information, conflicting records and approval decisions.

  3. 3. Review the results

    Document what passed, what needs fixing, and your team's go-live conditions.

See a digital twin example
PRODUCTION CRM · ERP · inbox · spreadsheets MIRROR DIGITAL TWIN + edge cases · synthetic failures agents are tested on the right before they touch the left FIG. 02 — DIGITAL TWIN TRIAL

Free playbook

Find out whether one workflow is worth automating.

This free, eight-page guide helps you spot delays, decide which tasks belong with rules, AI or people, and choose a sensible next step. Work through one recent case with your team, then use the included worksheet to decide: explore automation, fix a problem first, or leave the process as it is.

  • →Find where time is lost between steps, not just time spent doing the work
  • →Spot data problems and decide which actions need human approval
  • →Leave with a one-page worksheet and a clear next step

A practical starting point for your team. It does not replace a full paid feasibility audit.

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FIG. 03 — WHO IS RESPONSIBLE

  1. Your AI Automation Architect

    One accountable lead understands the workflow, designs the solution and coordinates delivery.

  2. Your team sets the boundaries

    You agree the scope, approval rules and conditions for going live.

Connect systemsIntegration developersPrepare dataData specialistsTest the workQuality assurance
See the delivery network
INTEGRATIONdevelopers DATAcleanup & pipelines QAsafe testing YOUR TEAMsign-off LEAD ARCHITECT one accountable owner FIG. 03 — DELIVERY MODEL

How Simplicate is built

One accountable lead, from assessment to rollout.

Your AI Automation Architect understands the work, designs the solution and oversees delivery. When the project needs specialist skills, we bring in vetted integration developers, data specialists and testers. You always know who is responsible.

Our roots are in business process automation. We start with your workflow and your data, then choose the tools that fit.

One accountable leadBusiness process automation rootsVetted specialist network

Before you ask

Straight answers.

The questions owners ask before getting started. If yours isn't here, it goes in the form below.

Do we have to replace our software?

We start with the tools you already use and look for ways to connect them. If a tool needs to change, the feasibility audit identifies the reason and cost before you commit to a build.

What does a feasibility audit cost, and how long does it take?

The Free Workflow Review is a short initial written assessment, with no commitment. Discuss a Project starts a consultation about scope and next steps. Neither is the full feasibility audit: that is a separate paid engagement with scope, deliverables, timing and price agreed before work starts.

Our data is a mess. Is that a dealbreaker?

Not necessarily. The assessment checks for missing, inconsistent or unreliable information. The recommendation may be to fix specific records or processes first, automate a smaller part of the work, or keep a step with a person.

What stops the AI from doing something expensive or embarrassing?

Agreed rules define which routine actions can run automatically and which decisions need approval. Checks look for missing information, unusual amounts and other conditions identified during design. Exceptions and consequential decisions go to a person. Testing checks those safeguards before rollout; they reduce risk, but do not make software infallible.

Who actually does the work?

One accountable architect owns the engagement end to end. Build capacity comes from a vetted network of integration developers, data specialists, and QA, scaled to the scope of the job. You always know who is responsible.

How do you handle access to our systems and sensitive data?

We agree what information and access the project needs before connecting to your systems. We request only the permissions needed for the agreed workflow and use sample or anonymized data for testing where practical. Before launch, we document where information goes, who can access it, and how project data will be retained or removed.

Will our information be shared with AI providers?

If a workflow uses an external AI service, we explain which provider is involved and what information it will receive, and obtain your approval before sending your business data. You can specify approved providers and data restrictions. We check the relevant service’s retention and model-training settings as part of the design. If your restrictions make an approach unsuitable, we discuss alternatives.

What happens if the automation makes a mistake?

We design for exceptions as well as routine work. Before launch, we agree which actions can happen automatically, which need approval, and what should trigger an alert or pause. We test representative failure cases and document how to stop the workflow and investigate problems.

Where the connected systems support it, we include a recovery or reversal process. Some actions—such as sending an email—cannot simply be undone, so we agree appropriate checks before those actions occur.

Who monitors the workflow after launch?

Each project has a named owner on your team. At handover, we explain how to check results, respond to alerts, and pause the workflow if needed. We agree who receives alerts and who is responsible for responding. Ongoing monitoring by Simplicate is available as a separately scoped support service.

What support is included after launch?

Implementation projects include 30 days of stabilization support from the agreed go-live date. This covers questions about the delivered workflow and fixes where our implementation does not behave as agreed.

New features, additional workflows, and changes caused by new requirements or third-party services are assessed separately. We explain any additional work and cost before proceeding.

How quickly will you respond to a support request?

During included or contracted support, we aim to acknowledge requests within one business day. Standard support hours are Monday–Friday, 9 a.m.–5 p.m. Eastern, excluding holidays agreed in your project or support agreement. This is an initial-response target, not a guaranteed resolution time.

We provide a documented pause procedure for urgent workflow problems. Faster response coverage can be agreed separately when the workflow requires it.

Can you support us after the first 30 days?

Yes. We can agree an ongoing support arrangement or provide help on a separately quoted basis. The scope can include monitoring, maintenance, and improvements. Your agreement sets out coverage hours and response targets so you know what to expect.

Start here

Start with your workflow.

Choose a Free Workflow Review for a short written initial assessment, or Discuss a Project for a 20-minute consultation about your goals, scope and next steps. We reply within two business days. A full feasibility audit is a separate paid engagement, with scope and price agreed before work starts.

  • Free Workflow Review: a short written assessment, yours to keep with no commitment
  • Discuss a Project: request a consultation; we will send times to arrange the call
  • Fixed-scope audits, priced before anything starts
  • To request a call, use the existing “I'd rather talk” option below
Prefer email? [email protected]

Get a Free Workflow Review

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Request received.You'll hear back within two business days with your free initial written workflow review. A full feasibility audit is separately scoped and priced.