AI that works inside the software your company runs on
Idaya builds AI into Salesforce, ServiceNow, Power BI, and your other core systems. Then we train each team to use it in their daily work and track whether they do.
Five practice areas
Each one covers the same three jobs: build AI into the tool, train the people who use it, and connect it to the systems around it.
Sales, marketing and service
We add AI to pipeline reviews, campaign builds, and customer service queues, then train sales reps, marketers, and service agents on the parts that affect their work.
Platforms: Salesforce, HubSpot, Adobe, Marketo, Commerce Cloud, Shopify, Slack, Teams
IT help desk
AI sorts, routes, and helps resolve tickets. Your team handles fewer tickets, answers faster, and keeps a record of how each one was closed.
Platforms: ServiceNow, Freshservice, Jira Service Management, Zendesk, Okta, Entra ID
Analytics and data
AI helps analysts write reports and helps engineers maintain data pipelines. We teach both groups to check its work before anything reaches a decision maker.
Platforms: Power BI, Tableau, Microsoft Fabric, Databricks, Snowflake
AI models and automation
Rules and training for the AI models your company already pays for: which model to use for which task, what data it may see, and what it costs.
Platforms: Anthropic, OpenAI, Microsoft Copilot
AI change management
The people side of a rollout. We prepare leaders and managers, explain the changes to each team in plain terms, and measure adoption by real use rather than course completions.
Where we fit
Many firms can set up a CRM or a help desk. We start where those projects usually end, with the people who open the system every morning.
What we do
- Build AI into the screens your staff already work in
- Train each role on its own tasks
- Measure whether people use what you bought
What we don't do
- Migrate your data, hand over logins, and leave
- Push one vendor. We work with the platforms you have.
- Run a single training day that ends with a certificate
Our approach
Building AI into software and getting people to trust it are separate jobs. We plan and staff them separately.
Embed
We put AI on the screens people use: a draft reply inside the ticket, a summary on the deal record before a call. Nobody has to open another tool.
Enable
Training follows the role. A sales rep, a marketer, and a help desk analyst each learn what changes in their own work, using their own records.
Extend
When the AI needs information held elsewhere, such as order history inside a support ticket, we connect the systems so nobody copies data by hand.
How an engagement runs
The same four stages apply to one team on one application or a rollout across the company.
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Discovery
We sit with reps, marketers, and agents and watch how they work today, not how the process document says they should.
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Plan
We agree where AI should appear, such as a record, a queue, or a briefing, and where it should stay out.
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Build and train
We build the connections and run training in parallel, so people are ready on launch day.
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Review
At 30 and 60 days we come back, look at usage data, and make changes.
What we do for each team
Pick a practice area to see the work role by role.
Sales teams
AI in pipeline reviews, call preparation, and deal risk alerts. We coach reps until checking it before a call becomes routine. Reps ignore features nobody showed them how to trust.
Marketing teams
AI help with audience segments, campaign briefs, and creative variations. Marketers learn to write clear prompts and to review the output before anything goes out.
Service and support teams
AI drafts replies, suggests next steps, and finds help articles, with rules for when a person takes over. Agents learn where it is reliable, so one wrong answer doesn't end their trust in it.
Sales and marketing operations
The AI follows your data structure, sharing rules, and permissions. Operations staff see which tasks run automatically, which get AI help, and which stay with people.
Onboarding and training leads
A repeatable onboarding plan, so new hires learn the software and its AI features together instead of finding the AI by accident months later.
Frontline analysts
AI drafts responses, suggests fixes, and sorts incoming tickets. Analysts learn when to accept a suggestion and when to override it.
Tier 2 and Tier 3 engineers
Escalated tickets arrive with full context and a first diagnosis attached, so nobody has to rebuild the story from a single line or chase a colleague for the logs.
Service desk managers
Response targets and queue rules rebuilt around what AI can resolve and what still needs a person, tested against your own ticket history.
IT and security leadership
A record for every ticket showing whether it closed automatically, with AI help, or by hand, detailed enough for a compliance review.
Report builders
AI helps write formulas and queries. Analysts learn to spot when a generated formula needs a manual check, so faster reports don't mean more errors.
Data engineers
AI helps debug pipelines, document changes, and review data structure updates. It speeds up existing work instead of adding another system to watch.
Analytics and data leads
Clear labels showing which figures came from AI, which are certified, and which await approval, so any number in a board pack can be traced.
Business users
Training for people who ask an AI assistant for numbers, so they check where the answer came from before acting on it.
IT and platform admins
Permissions set so a model answers only from data it should see. The setup is the same for Anthropic, OpenAI, and Microsoft.
Everyday users
Prompt training built on real tasks: a rep preparing for a call, an analyst building a report, an agent replying to a customer.
AI and platform leads
A written policy for which model handles which task, what it costs, and what happens when it is wrong, reviewed against actual use every quarter.
Security and compliance
A log of what each model was asked, what data it read, and what it returned, held to the standard of any other system with access to company data.
Executive sponsors
A short statement of what the rollout should change, how success will be measured, and what leaders need to say and do in public to support it.
People managers
Talking points, coaching guides, and a simple view of who on their team uses the AI and who avoids it, so they can step in early.
Frontline teams
Straight answers about what changes in their day and where to go when the AI makes a mistake. We raise worries about jobs openly and answer them.
HR and communications
One plan that keeps announcements, training, and role expectations in step with what is being released.
Program leads
Readiness checks before launch and usage tracking after it, so you can see which teams have changed how they work and which need more support.
About Idaya
Idaya AI is a US company. Our consultants have implemented Salesforce, commerce platforms, integrations, and analytics systems, and now focus on getting AI inside those systems adopted.
We work remotely across the US, the UK, and India. Clients get coverage across their working day, and we meet in person whenever a project needs it.
Industries we serve
Automotive, data centers, healthcare, medical technology, and financial services.
United States
San Francisco Bay Area, Chicago, and New Jersey
Bay Area office1111 Broadway, 3rd FloorOakland, CA 94607
United Kingdom
London and Cardiff
London office8 Devonshire SquareLondon EC2M 4YJ
India
Bangalore, Mumbai, and Noida
Bangalore officePrestige CubeSite No. 26, Laskar Hosur Road
Adugodi, Koramangala
Bangalore, KA 560029 Mumbai officeSpectrum Tower, Mindspace
Chincholi Bunder Road
Malad West, Mumbai
Maharashtra 400064
Tell us which systems your teams use
We'll set up a short call to find where AI can help your teams and where it shouldn't be used.