Operations lead and their teams
The people who run the busiest step need visual inspection to work on a normal Monday, not only in a demo with clean data.
AI & automation
Visual Inspection built for Indian businesses, with one accountable team.
Scope, build and run visual inspection with measurable outcomes - no vendor handoffs, no black boxes.
Map the current workflow and agree the smallest useful release. In practice this is the step the operations lead relies on when decisions must be right the first time.
Ship in two-week increments with a staging link you can click. In practice this is the step the operations lead relies on when review notes must be right the first time.
Payments, WhatsApp, email and accounting connected through documented APIs. In practice this is the step the operations lead relies on when prompts must be right the first time.
Code, accounts and runbooks transferred to your ownership. In practice this is the step the operations lead relies on when retrieved context must be right the first time.
The bigger picture
Visual Inspection sits inside our AI & automation practice. Scope, build and run visual inspection with measurable outcomes - no vendor handoffs, no black boxes. The useful question is not which platform to buy, but which decision or handoff the work should improve first.
Teams usually arrive with an LLM API, a vector store and the workflow engine already in place. The gap is rarely a missing tool; it is the undocumented step where prompts get copied between systems and someone compensates by hand.
We scope one measurable outcome, build it end to end, then extend based on evidence. Success is reviewed against task accuracy and human review time, with a working release every two weeks and a handover that leaves you in control.
The sections below describe how the engagement usually runs. Scope, integrations and timing are adjusted to your environment rather than copied from a standard package.
It works on curated examples but has no evaluation set, no fallback and no owner for bad answers.
Nobody can say which data may leave the system, which model sees it, or how it is retained.
Agents act on low-confidence cases because the escalation rule was never written down.
Changes are made directly in production with no versioning, tests or audit trail.
Token spend is reviewed after the invoice, not per workflow or per customer.
Preparing a review means exporting from the workflow engine and reshaping it by hand, so the numbers are always a little behind the decision.
When a step fails, operations and the next team both assume the other one owns the fix.
There is no dependable record of who changed review notes or why, which is exactly what an auditor asks for first.
Who this is for
The people who run the busiest step need visual inspection to work on a normal Monday, not only in a demo with clean data.
Teams that need the same process, permissions and reporting across sites without a manual consolidation exercise at month-end.
You have added people and volume, and the spreadsheet that once worked is now a risk that only one person fully understands.
Leaders who need AI-assisted operations to behave consistently when a new hire, a new branch or a new client joins.
Teams that want a partner to ship the first release, document the decisions and leave a codebase they can extend.
People who need evidence on demand: who accessed what, which approval was given, and how long records are retained.
Small teams that need working software in weeks, with a scope they can defend to a client or an investor.
Organisations replacing the workflow engine without pausing the business or losing historical prompts.
Inside the scope
Explore what goes into visual inspection.
Map the current workflow and agree the smallest useful release. In practice this is the step the operations lead relies on when decisions must be right the first time.
Ship in two-week increments with a staging link you can click. In practice this is the step the operations lead relies on when review notes must be right the first time.
Payments, WhatsApp, email and accounting connected through documented APIs. In practice this is the step the operations lead relies on when prompts must be right the first time.
Code, accounts and runbooks transferred to your ownership. In practice this is the step the operations lead relies on when retrieved context must be right the first time.
Daily and weekly views built on the same records the team already maintains, so operations, data and support teams stop rebuilding spreadsheets before every review. The measures are chosen with you - typically task accuracy and human review time - and reviewed against a baseline agreed at kickoff.
Access is granted by role and location, with a record of who viewed or changed prompts. Sensitive approvals are separated from routine edits, and break-glass access is logged so an urgent exception does not become an invisible one.
Existing prompts, retrieved context and balances are inventoried, mapped and imported in a dry run before switchover. You get a reconciliation report and a read-only window on the old system, so a question about an old record does not stall the rollout.
Documented connections to a vector store and the workflow engine, plus internal tools for reminders and updates. Each integration has an owner, a failure mode and a retry path, instead of a webhook that silently stops delivering.
How we work
We map the current AI-assisted operations, interview operations, data and support teams and record where prompts is retyped. The output is a short written scope with one primary success measure and an explicit out-of-scope list.
We choose the architecture and integration approach, including what to connect first, what to leave manual and how prompts will be governed. Trade-offs are documented rather than hidden in a diagram.
A working release ships every two weeks with a staging link. Reviews focus on real usage - exceptions, permissions, edge cases and the reports the team actually reads - not a feature checklist.
Connections to a vector store and the workflow engine are tested with representative data. We run an acceptance pass against the agreed metrics and fix the issues that block adoption before widening the rollout.
One team uses the release for real work while others continue as before. Training is role-based, and the runbook is written for the team that inherits the system.
Code, environments, documentation and credentials are transferred. We review task accuracy and human review time after launch, then agree the next increment only if the evidence supports it.
Why Synnotech
We start from how operations, data and support teams work today, then build visual inspection around the handoffs that cause the most friction. The roadmap is chosen by evidence, not by a feature catalogue.
Design, build, hosting and support sit under one roof. When something crosses a boundary, there is no vendor ping-pong and no gap where responsibility quietly disappears.
Every two weeks there is a deployed release and a short written note on what moved, what did not and why. The measures are agreed up front - task accuracy and human review time - and reviewed after launch.
Code, accounts, documentation and runbooks are transferred to you. Support is a choice you make, not a dependency we design into the system.
Controls are written into the schema and the interface, with awareness of DPDP Act 2023 and EU AI Act expectations. We do not sell certification, and we do not pretend software alone creates compliance.
What you receive
One page that says what ships in visual inspection, what does not, and how task accuracy and human review time will be measured against a baseline.
A practical map of how prompts moves between operations, data and support teams, including the exceptions that never appear in a requirements document.
A deployed release covering the core flow, with a staging link, a short walkthrough and a rollback path that has been tested.
A dry run, a reconciliation report and a read-only window on the old system, so historical prompts remains answerable after switchover.
Documented connections to a vector store and the workflow engine, with credentials, failure modes, retry behaviour and an owner for each.
A readable matrix of who can view, edit, approve and export, including the break-glass path for urgent exceptions.
Setup, deploy, backup, restore and rollback steps written for your team, including the small details that usually live in someone's head.
Short sessions for operations, data and support teams, with recorded walkthroughs and a one-page cheat sheet per role rather than a generic manual.
Architecture notes, data dictionary, API references and decision records, organised so a new hire can find the reason behind a choice.
Access logs, approval trails and retention settings aligned with DPDP Act 2023, presented in a form your team can hand to a reviewer.
Code repository, environments, domains, credentials and third-party accounts transferred with a checklist both sides sign.
A named contact, a response window and a short feedback loop, with monitoring and backup checks included if you choose ongoing support.
Business value
Treated as a success measure from the first workshop, then reviewed again four weeks after launch and documented against the baseline.
Tracked in the same operational report the team already reads, so the improvement is visible without a separate study.
Written into the handover notes with the baseline, the measurement method and the person who owns the review.
Fewer retyped prompts and fewer reconciliation exercises, because the same record drives the next step instead of being copied into it.
Each handoff has a named owner and an escalation path, so a stalled item is visible before it becomes a customer complaint.
Daily and weekly views built from the operational record, so task accuracy is available during the review rather than after it.
Access and approval history for prompts is attributable and retained, which shortens internal reviews and external questionnaires.
Documentation and runbooks reduce the number of processes that only work because one person remembers how.
The intended outcome
Scope, build and run visual inspection with measurable outcomes - no vendor handoffs, no black boxes.
Security & compliance
Role-based access with per-module permissions and an audit trail for every view and edit of prompts.
Encryption in transit and at rest, with a documented key-management and retention process aligned with DPDP Act 2023.
Consent and data-sharing rules that reflect how prompts is collected, used and shared across teams.
Configurable retention for prompts and retrieved context, including a defensible deletion process.
Separation of duties for sensitive approvals, with break-glass access that is logged and reviewed.
Backups, restore drills and a written incident-response path, rather than an untested assumption that recovery works.
Awareness of EU AI Act expectations and sector-specific AI guidance, applied to the scope of the system rather than claimed as a certification.
A 30-minute call and a written scope before any work begins.
Most engagements ship a working first release in 4-6 weeks. The exact window depends on how many systems need to connect and how clean the existing prompts is. We agree the first release in writing before work starts.
Most first releases are a fixed fee with a fixed scope, agreed after the discovery workshop. Later phases are priced separately so you can stop, continue in-house or bring in another partner without renegotiating the whole programme.
Yes. We start with a short audit of an LLM API, a vector store, the workflow engine and the data that moves between them. Where an integration is missing, we document the workaround and decide whether to build a connector, change the process or leave it alone.
You do. Repositories, cloud accounts, domains, credentials and third-party subscriptions are transferred at handover, along with the documentation needed to operate them without us.
We inventory the sources, define merge rules for prompts, run a dry-run import, reconcile counts with your team and only then switch over. The old system stays read-only for a defined period, so an old record can still be checked.
Expect one working session per week with the people who own the process, plus a short review at the end of each increment. The operations lead who uses the system every day is the most important reviewer, not the steering committee.
Yes, on a monthly retainer with a defined response window, monitoring, backups and a named contact. Support is optional; the handover is designed so you are not locked in.
We review task accuracy and human review time against the baseline, fix the issues that block adoption, and agree a short list of next modules. The next phase is chosen by measured value rather than by the original roadmap slide.
If a product fits the way operations, data and support teams work, we will say so. A custom build makes sense when the workflow is a competitive advantage, when integration is the hard part, or when the available tools force a process your team does not actually want.
Let's work together
Tell us what you are building or what needs to work better. We will help you define the next step.