AI Innovation and Automation Workshop
The AI Innovation and Automation Workshop is a diagnosis led by Cassi.ai in three one-hour sessions. It maps how work actually happens in each area of the company, measures how mature the company is in using AI, and ends with a prioritized automation and AI plan delivered in an executive report. It is built for research firms, agencies, research, innovation and insights teams, and service companies that have an innovation agenda and no plan for it.
How it is done today
AI usually arrives as a tool before anyone maps the work. Someone tries an AI assistant, the company subscribes to one or two tools, each area tries to fit them into a routine that still runs on spreadsheets, email and people's memory, and the test runs with no owner, no metric and no baseline. The results: tools bought without a map of the process, pilots that never leave the pilot, and automation of the wrong task. When a bottleneck comes from a bad rule or from information lost between areas, automating the current flow only makes the error happen faster.
Format
- Session 1, discover and map (60 minutes): business, clients and services; the operation end to end; manual tasks, rework, waiting and lost information; what the company wants to change in the next 12 months.
- Between sessions, 360 diagnosis by area: in each area the team picks the activities that weigh most and records context, pain and friction, data and tools used, and the decision that depends on it. Areas follow the company's sector.
- Between sessions, AI maturity: 43 questions across 10 dimensions, each scored from 0 (nonexistent) to 4 (scalable). A 3 or a 4 requires an example, an owner and a way to verify it.
- Session 2, explain and prioritize (60 minutes): opportunities drawn from recorded pains, rated on impact, effort, feasibility, urgency and return, and placed in act now, prepare, experiment or monitor.
- Session 3, decide and plan (60 minutes): a plan in three horizons (0 to 3, 3 to 6 and 6 to 12 months), the first pilot, next steps and pending decisions.
What the company receives
- AI maturity level from M0 (aware) to M4 (adaptive), with the strengths the company can lean on.
- The limiting dimensions, and the step that moves each weak question up one level.
- A map of activities by area: recurring bottlenecks, tasks that depend on one person and manual hours at stake, labeled as estimates.
- A route for each opportunity: improve the process, buy a platform, configure AI agents or build a proprietary solution.
- A prioritized list in act now, prepare, experiment or monitor.
- A 30, 60 and 90 day capability plan and the path from 0 to 12 months, with the first pilot defined.
- An interactive report and a PDF executive report. Every conclusion points to the answer behind it, and the consultant reviews everything before publishing.
Methodology
Six analysis lenses, always in the same order: strategy and value; capabilities and customer journey; real flow and bottleneck; cause and improvement; automation and AI; portfolio and adoption. Each lens is backed by recognized methods such as Jobs to Be Done, Business Model Canvas, Value Stream Mapping, BPMN, DMAIC, root cause analysis, CRISP-DM, the NIST AI Risk Management Framework, RICE and ADKAR. Automation comes in after the likely cause of a bottleneck is confirmed.
Products the plan can point to
When an opportunity calls for a ready product, the plan can point to one of the Cassi.ai products.
- Deskor: Connects company knowledge, AI agents and workflows, so the team builds proposals, decks, reports and dashboards from what the company already knows.
- QualiLab: Automates qualitative analysis. Focus groups and interviews go in. The report and the deck come out, with a verbatim behind every finding.
- Dash Lab: Builds made-to-measure research dashboards: matrices, segmentation, driver analysis, significance testing and tracking, with the base next to every number.
- Survey QA: Automated survey testing. A robot walks every screen on desktop and mobile and returns a verdict screen by screen, with screenshots.
- Survey Studio: Immersive research. Every study gets its own format, such as gamified missions or a narrative in scenes, on one engine with a live fieldwork cockpit.
- Synthetic Lab: Turns the research already done into synthetic personas of the target, for synthetic focus groups and quantitative studies with quotas.
- Synthetic Vertical Simulator: Rebuilds the client's consumers as synthetic personas from the client's own data and places them in a virtual copy of the environment where the decision happens.
- Video Lab: Analyzes ethnographic and in-home test videos and returns behavioral KPIs. Every conclusion carries a timestamp and a frame as evidence.
- Shopper Insight Lab: A virtual shelf purchase simulator. Participants shop a virtual aisle with a cart and a budget, and the dashboard shows attention, choices and trade-offs.
- Review Pulse: Compares a chain's stores with competitors from public data: hourly foot traffic, Google reputation and review topics, store by store.
- Shelf-Lab: Measures who passed, stopped, touched and took each product at the shelf, using the CCTV the store already has. Heads are blurred at the source.
- Community Lab: A networking platform for events that connects clients and participants, integrated with the CRM. It shows a live map of who is there and who to talk to, with the reason.
Start
Pricing is not published: products are available as SaaS on credits, per project or as a platform purchase, and the format is agreed in conversation. To discuss the workshop, use the contact form at https://www.cassiai.com/contact.