7UNIT / AI AUTOMATION
AI AUTOMATION
AI automation built around how your business actually works.
7Unit builds one workflow and connects it to WhatsApp, email, CRM, ERP or your internal software. AI where judgement is useful. Deterministic software where rules are enough. Human control where consequences matter.
7Unit operates from Bengaluru and Dubai, and works with businesses across India and international markets.
PROOF FROM SYSTEMS ALREADY RUNNING
Proof from systems already running
We link only work documented on this site. These are engineering patterns, not a promise that your numbers will match a previous client.
Practical AI assistants
Production assistants, including WhatsApp inquiry agents. The assistant has to keep the thread, hand off with context, and keep working when the model fails. 7Unit engineered session memory, human handoff with the conversation intact, per-tenant cost attribution, and graceful degradation when the model layer fails.
Read the AI assistants caseCloser CRM
A WhatsApp-native CRM for UAE sales teams. The CRM lived somewhere else, so deals, conversations and follow-ups were split, and people either retyped them or did not. 7Unit engineered pipeline, qualification, follow-up and assignment inside the thread, with human takeover and every automated action logged against the deal.
Read the Closer CRM casePingbot
An AI WhatsApp assistant 7Unit builds and operates. Customers message when staff are not there. Pingbot answers, qualifies and books on that number, on the same rails as Closer CRM.
See Pingbot7Unit AgentOps
Running inside 7Unit, on tools the team already uses. Agents need an approval gate and a record of each action. Proven in our own engineering workflow: approvals, audit logs and observability are part of the system.
Read about AgentOps
THE OPERATIONAL PROBLEM
The work is already happening. It is just not in one system.
The opportunity is not to add AI. It is to find the steps where a model and ordinary software can take repeat work off a person, without guessing at a decision that should stay human.
WhatsApp and email
Customer and internal requests arrive in threads. Context stays with whoever read them last.
Spreadsheets and inboxes
Status, exceptions and follow-ups live in files and shared mail, not in a system of record.
CRM, ERP and internal software
The tools exist. People still copy fields between them, or skip the update because the conversation is elsewhere.
Support queues and approvals
Routing, chasing and sign-off depend on someone noticing. When they do not, the work waits.
CAPABILITIES
What we automate
These are patterns we have engineered in production systems. We scope the ones that match your workflow. We do not sell a catalogue of bots.
Customer inquiry handling
WhatsApp and messaging agents that keep session context, qualify a request, and hand off to a person with the thread intact.
Document intake and extraction
Classification and extraction for document-heavy operations, with a person reviewing the exceptions rather than every file.
Workflow routing
Requests moved to the right queue, role or system based on rules you can read, not a hidden prompt.
Internal knowledge assistance
Assistants grounded in your procedures and tools, used by the team that already does the work.
Sales and CRM workflows
Follow-up, qualification and pipeline updates on the surface where the conversation already happens.
Back-office repetition
Status changes, notifications and data movement that a person currently retypes between systems.
Decisions with approval
The model prepares a recommendation or a draft. A person approves anything that changes money, compliance or a customer commitment.
HOW 7UNIT WORKS
How we approach an automation
Not every step should be AI. The useful work is deciding the boundary, then engineering the path that stays reliable when the model is uncertain or unavailable.
- 01DiscoverWe sit with the people who run the process and name the outcome, the volume and the failure that hurts.
- 02Map the workflowInputs, systems, handoffs and the places context currently drops. Written down before anyone picks a model.
- 03Set the automation boundaryWhich steps are rules, which steps can use a model, and which steps stay manual. If a rule is enough, we do not wrap it in a prompt.
- 04Build and integrateThe automation is wired into the systems you already operate. It is not a separate chat window beside them.
- 05Put controls on the loopHuman approval, audit of actions that change state, and a defined handoff when confidence drops.
- 06MeasureAgainst the baseline and success criteria from discovery: cycle time, missed handoffs, cost of model calls, or exception rate.
- 07Operate and improveObservability, fallback when a provider fails, and a handoff your team can run. Then the next workflow, if the first one earned it.
HOW THE SYSTEM IS BUILT
Agents plus deterministic engineering
Production automation is rarely a chatbot. 7Unit combines a model with the software around it, so the system still behaves when the model is wrong, slow or down.
- AI / LLMs
- APIs and integrations
- Business rules
- Existing systems
- Human approval
- Observability
ENGAGEMENT
Start with one workflow
Buy an operational outcome, not a bucket of developer hours. We do not offer financial guarantees.
One workflow, named
We start from a single operational path, not a platform rewrite.
A system of record
The automation writes to the tool that should own the work, instead of creating a side inbox.
A human boundary
Approvals, exceptions and low-confidence cases escalate with context, not a cold restart.
What we identify before we scope
- Start with one workflow.
- Map the current process and the systems it already uses.
- Define the automation boundary, and where a person stays in control.
- Agree the success criteria.
- Scope the engineering required to reach that outcome.
USE CASES
Where this tends to start
Inquiries that never reach a record
Leads or support requests arrive on WhatsApp or email. Someone is supposed to copy them into a CRM. Some of them never get there.
Documents waiting on a person
A batch of files has to be classified or extracted before anyone can act. The backlog is the process.
Follow-up that lives in memory
A salesperson or operator knows who to chase, until they do not. The next step is not in the system.
Approvals stuck in chat
A request is ready, but sign-off is a message in a thread. The audit trail is whoever remembers the conversation.
INTEGRATIONS
Systems we connect
The automation sits on the tools the business already uses. Exact integrations are scoped per workflow. Typical surfaces:
- CRM
- ERP
- Spreadsheets
- Support tools
- Internal APIs
- Document stores
Questions buyers ask
What can an AI automation company automate?
Repeat operational work with a clear input, a system to write to, and a rule for when a person must decide. For 7Unit that has included inquiry handling, document intake, CRM follow-up, routing and internal assistance. We do not automate a process we have not mapped, and we do not put a model on a step that a deterministic rule should own.
How is AI automation different from traditional workflow automation?
Traditional workflow automation moves data and triggers actions with rules. AI automation adds a model where the input is unstructured: language, documents, or a judgement that can be drafted and then checked. Most production systems need both. If the step is already a rule, adding a model only adds cost and a new failure mode.
Can you integrate AI with our existing CRM or ERP?
Yes. The usual design keeps your CRM or ERP as the system of record and lets the automation read and write through its API. We have done this with messaging-led CRMs and with back-office systems such as Odoo. Replacing the system is a separate decision, and often the wrong first one.
Do we need to replace our existing software?
No. The first automation should meet the tools people already use. We replace software only when it cannot safely hold the workflow, and we say so before the build.
How do you handle sensitive business data?
We design the control path before a model sees operational data: what may be sent, what must stay in your systems, who can approve an action, and how calls are logged. Client data is not treated as training material. Model and provider choices are documented. Regulatory interpretation stays with your counsel. We do not claim a certification the engagement has not earned.
Can we start with one workflow?
That is the engagement we prefer. One process, a baseline, a desired outcome, the systems involved, the control boundary, and success criteria. The engineering is scoped to that outcome.
How long does an AI automation project take?
Start with one workflow. We map the process, the systems and the control boundary before a build is committed. A contained workflow with a clear system of record can move quickly. One that crosses several systems, handles sensitive data, or needs tight human control takes a deeper look first. Build milestones are agreed after that map. We do not promise a universal delivery time.
Do you build custom AI agents?
Yes, when an agent is the right shape for the workflow. Custom here means wired to your tools, with approval, audit and a fallback. It does not mean a general-purpose chatbot with your logo on it. Governed agent work is described on the AgentOps page.
CONTINUE