01 · Value
A number the business cares about
The workflow consumes meaningful time, delays revenue, creates avoidable errors or limits capacity. Its likely benefit is large enough to cover implementation, operation and review.
AI automation consulting · workflow automation
Automate one costly workflow. Prove what changed.
Binarify redesigns and implements AI-assisted workflows inside the systems your team already uses.
We begin with the work: what arrives, who handles it, where it waits, what can go wrong and which number should move. Then we decide where ordinary rules, integration, AI and human review each belong.
30-minute discovery call · implementation from $15,000 USD
Choose the first workflow
A good automation candidate is valuable, repeated and testable.
A visible backlog can be frustrating without being worth automating. We look for a workflow whose volume and economics justify the build, and whose outputs can be checked before they affect a customer, employee or financial record.
02 · Feasibility
Inputs and outcomes we can inspect
Examples exist. The relevant information can be accessed lawfully. A domain owner can explain correct, incorrect and exceptional outcomes.
03 · Control
Errors can be found and recovered
The system can show its source, validate critical fields, route uncertainty and preserve a person’s authority where consequences are material.
Where AI automation helps
Common workflows, with a specific measure for each.
The same technology can create very different business results. The workflow and its baseline determine whether it is useful.
Enquiry and ticket triage
Identify the request, retrieve the relevant account context, suggest a response and route exceptions.
Measure time to first useful response · reassignment rate · unresolved backlog
Document intake
Extract required fields, validate them against rules and existing records, and send uncertain items for review.
Measure handling time · correction rate · cost per accepted document
Quotes and proposals
Assemble a draft from approved prices, terms, past work and the current request, with assumptions made explicit.
Measure request-to-send time · revision time · approved quote conversion
Internal knowledge
Retrieve answers from current policies and operational documents, show the source and record unanswered questions.
Measure time to answer · answer acceptance · unresolved question rate
Onboarding and handovers
Collect the required information, create tasks in the right systems, draft routine communications and expose missing steps.
Measure signed-to-live time · missing-item rate · manual follow-ups
Operational reporting
Collect agreed data from source systems, apply consistent definitions and draft commentary for a person to review.
Measure preparation time · corrections · reports delivered on schedule
Process before product
Rules, integration, AI and people each have a job.
AI is useful for language, documents, classification and drafting when the input varies. It is not the right mechanism for every step.
- Use deterministic rules for calculations, required fields, permissions, thresholds and known routing.
- Use integration to move approved data and actions between systems without retyping.
- Use AI where the workflow must interpret unstructured text or prepare a context-sensitive draft.
- Use human review where ambiguity, customer impact, money, employment or regulatory obligations make judgement important.
This division makes the workflow easier to test and maintain. It also gives the team a clear answer when they ask which decisions remain theirs.
The engagement
From a costly process to an operated workflow.
Map and measure
Follow real work through the current process. Agree definitions, volume, handling time, delay, error cost and the metric that will be measured again.
Check what you already own
Review your software edition, permissions, APIs, data quality and existing automation. Configuration may solve the problem without a custom build.
Design the controls
Define source material, validation, access, retention, approval, exception handling, logs and the conditions that stop or roll back an action.
Build and evaluate
Connect a contained path, test representative and difficult cases, record failures and let the workflow run in a controlled mode before expanding access.
Adopt and prove
Train the people doing the work, monitor actual use, measure exceptions and take the agreed operational metric again using the same method.
What the business case includes
Faster is useful only when the whole workflow improves.
We count the time people spend checking and correcting the output. We include model, software, messaging and support costs. We distinguish capacity released from cash saved, and revenue influenced from contribution profit.
A result is reported against the signed-off baseline. If volume, staffing or the definition changes, that change is recorded rather than hidden inside the comparison.
How to prove an AI project worked →Industry workflow libraries
See how the method applies to work your team recognises.
Practical questions
Before commissioning AI workflow automation.
What does an AI automation consultant actually do?
We map how a workflow runs today, identify where judgement or language work can be assisted, check what your current software already supports, and design the integrations, rules and human approvals needed to operate it. We then establish the baseline, build a contained implementation, train the team and measure the same workflow again.
Which workflows are suitable for AI automation?
Good candidates have repeated volume, a recognisable input and output, recoverable errors, accessible data and an owner who can review the result. Examples include document intake, enquiry triage, proposal preparation and internal knowledge retrieval. A rare process with unclear decisions or severe consequences from one mistake is usually a poor first project.
Do we need to replace our CRM, ERP or helpdesk?
Usually that is not the starting point. We first assess configuration and integration options in the systems you already use. A replacement is considered only when a system prevents the agreed outcome and the business case supports the disruption and cost.
Can you automate a workflow from beginning to end?
Sometimes, but full automation is not assumed. We separate deterministic steps, AI-assisted judgement and decisions that require a person. Approval points depend on the cost of an error, reversibility, customer impact and your risk tolerance.
How do you measure whether the automation worked?
Before implementation, we agree an operational metric and its calculation method. Depending on the workflow, that may include cycle time, handling time, correction rate, backlog, response time, conversion or cost per completed item. We also record review time, exceptions, software cost and adoption so that a faster step is not mistaken for a profitable result.
How much does AI workflow automation consulting cost?
The AI Impact Diagnostic starts at $2,500 USD and normally takes one to two weeks. Implementation sprints start at $15,000 USD. The diagnostic fee is credited against the sprint if you proceed. The scope, fixed price, milestones and expected running costs are agreed before implementation begins.
Can you work with a company outside India?
Yes. Delivery is remote, with working hours agreed for the engagement. We primarily serve growing businesses in the United States, United Kingdom, Canada, South Africa, Australia, the UAE and Singapore. Data handling, access and any country-specific requirements are reviewed during discovery.
Bring one workflow, not an AI shopping list.
Tell us what enters the process, who handles it, where it waits and what a mistake costs. The first call is to establish whether there is a useful next step.
No confidential records are needed for the first call. Meet Perumal, who leads each engagement.