How is this different from the RPA we tried before?

Classic RPA drives a user interface, so it breaks whenever the screen changes and it cannot handle anything ambiguous. The current generation works through APIs where they exist and uses models for the judgement steps that previously forced a human handoff - reading an unstructured document, classifying an exception, drafting a response. We still use UI automation where a system genuinely has no API, but as a last resort rather than the default, because that is where the maintenance burden comes from.

What happens when the automation gets something wrong?

That is a design decision made at the start, not an incident response. Every automated path has a confidence threshold and a defined fallback - route to a human with context assembled, or hold and escalate. We tune the automation rate deliberately: pushing it higher increases throughput and error rate together, so the right level depends on the cost of a mistake in that specific process. You control that dial, and every decision records why it went the way it did.

Which processes are worth automating?

High volume, well-defined, and currently consuming skilled people on unskilled work. The ones to avoid are processes that are about to change, processes nobody can describe consistently, and processes where the exception rate exceeds roughly a third - automating those encodes confusion rather than removing it. We usually recommend fixing the process before automating it, which occasionally means the automation is no longer needed.

Do you replace people with this?

In our engagements the pattern is almost always redeployment rather than reduction - the automation takes the repetitive volume and the same team handles exceptions, quality and the work that was backlogged. We say this plainly because it affects adoption: if the people who understand the process believe they are automating themselves out of a job, they will not give you the edge cases, and the edge cases are where these projects fail.

How long before we see a return?

A single well-chosen process typically pays back within two to three quarters. We deliberately start with one process end to end rather than a platform rollout, because the first one teaches you what your actual exception rate is - which is invariably higher than anyone estimates. Platform-first automation programmes tend to produce impressive tooling and few automated processes.

SyncTrix

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Service · Intelligent Automation

Automate the volume, route the judgement.

AI agents, document processing and workflow automation with explicit confidence thresholds and human fallback - so the automation rate is a dial you control rather than a property you discover in production.

Book a strategy call See capabilities

API-first, not screen scrapingHuman fallbackAuditable decisions

2-3 qtrs

Typical payback on a well-chosen process

One process

Where we start, end to end, before any platform

Every decision

Recorded with the reason it went that way

You set

The automation rate and the fallback threshold

Capabilities

What we actually deliver.

AI agents & orchestration

Agents that call real systems through real interfaces, with scoped permissions and confirmation on anything irreversible.

Tool-calling against real APIs
Per-user permission scoping
Confirmation on destructive actions

Document processing

Extraction from invoices, claims, contracts and forms - with an explicit way to say 'not present' rather than inventing a plausible value.

Structured extraction with schemas
Confidence scoring per field
Explicit uncertainty, not fabrication

Workflow automation

End-to-end process automation through APIs where they exist, with UI automation only where a system genuinely has no other route.

API-first integration
Exception routing with assembled context
UI automation as a last resort

Decision automation

Rules and models applied to routing, triage and approval - with the reasoning recorded so an auditor or a customer can be answered.

Explainable decision records
Rules before models where rules suffice
Threshold tuning per process

Evaluation & monitoring

Accuracy measured continuously against real outcomes, because an automation that silently degrades looks identical to one that works.

Ground-truth evaluation sets
Drift and accuracy alerting
Exception-rate trend tracking

Controls & governance

Audit trails, access control and the guardrails that make automated decisions defensible in a regulated process.

Immutable decision audit trail
Prompt-injection containment
Regulator-ready evidence

How we engage

A sequence that de-risks delivery.

Pick the right process

High volume, well-defined, currently consuming skilled people on unskilled work. We say no to processes about to change or nobody can describe.

Fix the process first

Automating a confused process encodes the confusion. Occasionally this step removes the need for automation entirely, and we say so.

Build one end to end

One process fully automated, including the fallback path - because the first one reveals your real exception rate, always higher than estimated.

Tune, then extend

Move the automation-rate dial deliberately against measured error cost, then apply the pattern to adjacent processes.

Outcomes

What clients measure afterwards.

Backlogs cleared

Repetitive volume absorbed so the team handles exceptions and quality instead.

Days to minutes

Cycle times on document-heavy processes like claims and onboarding.

Error cost controlled

Automation rate tuned against the real cost of a mistake in that process.

People redeployed

The pattern is redeployment to higher-value work, not headcount reduction.

Proof

Work we have actually delivered.

HRMS & biometric attendance

Built HR & payroll software with reliable biometric attendance.

155: Pages · 140 API routes
47: Data models (Prisma)

Read the case study

Civic-tech analytics platform

Built a waste-management dashboard that turns field audits into decisions.

4-tier: Role-based access control
10: Dashboard views · 19 APIs

Read the case study

Stack

Tools we work fluently in.

Models & agents

Claude
OpenAI
LangGraph
Temporal
Tool calling

Document AI

Textract
Document AI
Azure Form Recognizer
Structured outputs

Workflow

Temporal
Camunda
n8n
Airflow
Custom orchestration

Evaluation

Ground-truth sets
LLM-as-judge
Drift monitoring
OpenTelemetry

Why SyncTrix

Senior engineers, accountable outcomes.

API-first, not screen scraping

Classic RPA drives a UI and breaks when the screen changes. We integrate through interfaces, using UI automation only where nothing else exists.

The automation rate is your dial

Throughput and error rate rise together. We tune deliberately against the cost of a mistake in your process rather than maximising coverage.

We are straight about jobs

If the people who know the process think they are automating themselves out of work, they withhold the edge cases - and edge cases decide these projects.

One process before any platform

Platform-first programmes produce impressive tooling and few automated processes. We prove one end to end, including the fallback path.

FAQ

Questions, answered.

The questions COOs, heads of operations and transformation leads ask us most often before an automation programme.

Classic RPA drives a user interface, so it breaks whenever the screen changes and it cannot handle anything ambiguous. The current generation works through APIs where they exist and uses models for the judgement steps that previously forced a human handoff - reading an unstructured document, classifying an exception, drafting a response. We still use UI automation where a system genuinely has no API, but as a last resort rather than the default, because that is where the maintenance burden comes from.

Next step

Book an automation call - leave with a candidate process.

A 45-minute session with a senior engineer. We look at your highest-volume manual processes and identify which one is genuinely worth automating first - and you leave with that assessment, whether you engage us or not.

Book the call Explore all servicesAgents · Document AI · Workflow

Contact

Tell us about your project.

Briefs, NDAs, architecture reviews, anything goes. A senior engineer responds within 24 hours.

Email
[email protected]
Phone
+91 99228 74956
Locations
Hyderabad · Pune · Bangalore

What happens next

1 · A senior engineer reviews your brief within 24 hours.
2 · We schedule a 30-minute discovery call.
3 · You receive a written proposal in 48-72 hours.