Workflow and use-case discovery
Identify repetitive work, information gaps and handoff problems. Choose a bounded first use case with a clear owner, success measure and fallback.
Services / BigShark SEO
AI IntegrationWith the bigger picture in mind.
Useful AI, connected to the way your business works. We build assistants, voice experiences and account integrations around clear tasks, reliable information and human oversight.
Built around your business
Start with what
needs to change.
For teams with a specific task to improve, reliable source information and someone responsible for the outcome. We help choose an appropriate first use case rather than adding an assistant without a clear job.
The workflow is designed around what the system may know and do. We define the sources, permissions, review points and failure path, then test realistic requests before expanding. The team receives a practical operating model for information updates, monitoring and escalation so the integration remains useful after the initial demonstration.
How we measure the work
Evaluate task completion, answer quality, human handoffs, errors and operating cost. A working prototype is followed by an agreed evaluation before a broader rollout.
The scope, made clear
What we deliver.
Knowledge-connected assistants
Organise approved business information so an assistant can answer relevant questions. Define what it may answer, what it should cite and when it must hand over.
Voice agents and conversations
Design spoken journeys that suit the audience and supported language. Test pronunciation, interruptions, missing information and transitions to a human.
Account and tool integrations
Connect appropriate business tools through their supported interfaces. Keep permissions scoped and distinguish reading information from taking an action on an account.
Evaluation and failure handling
Test realistic requests, unsupported questions and integration failures. Record the expected response so quality can be checked again after a model or workflow changes.
Monitoring and operating costs
Track usage, response quality, errors and the cost of running the system. Give the team a way to update information and pause a workflow.
AI IntegrationBIGSHARK / CASE RECORD
2Live voice agents
English and Hindi, answering calls on this website
BigShark (own systems)
Inside the work
AI that is part of our own working business.
Our own-system case documents English and Hindi voice agents, integrations connected to advertising and store accounts, and a content production system. The record explains the implemented scope.
Read the case studyExplore the work.
From brief to delivery
A clear way forward.
Choose the useful problem
Map the task and current process. Confirm the source information, decision owner and boundaries before choosing a model or tool.
Prototype the interaction
Build a narrow working prototype using representative inputs. Test the conversation and the handoff before expanding the integration.
Connect and evaluate
Add the agreed data sources and tools, verify permissions and test expected responses alongside likely failure cases.
Launch with ownership
Document operation, monitoring and escalation. Review real usage with the team and improve the system through measured changes.
A few useful answers.
What AI work has BigShark SEO actually built?
Our own-system case documents English and Hindi voice agents, integrations with advertising and store accounts, and a content production system. The case explains the scope of the systems we built for our own operations.
Can an assistant use our existing documents and systems?
Often, yes. We first check the quality of the information, supported integration methods and access requirements. Sensitive information, update frequency and the consequences of an incorrect answer influence the design. The initial scope names the specific sources and tools that will be connected.
Will AI take actions automatically?
Only within the workflow and permissions you approve. Reading an account, preparing a draft and changing a live record are different capabilities. We define which actions require human review and provide appropriate logs, failure handling and controls for the agreed use case.
How are ongoing costs and quality managed?
Costs depend on usage, model choice, voice services, hosting and connected tools. We estimate these during scoping and monitor them after launch. Quality checks use representative tasks and recorded failure cases, with a named owner for content updates and operational decisions.