[ AI Copilot Development ]
We build assistants that live inside your SaaS or internal tool, see what the user is working on and help them finish it with suggestions and real actions. Every action runs with the user's own permissions and can be undone.
Analytics
Configuration
Support
Writing
Knowledge
FinanceCopilots earn their place when your product is powerful but complex, and users lose time finding the right screen, setting or data.
Users ask questions in plain language about the dashboard they are viewing, and the copilot runs the query, builds the chart and explains the change.
More users get value from your data features
A good copilot understands where the user is, offers help at the right moment and can actually do things. We design all three.
Context awareness
The copilot knows the current page, selected record, user role and recent activity, so users do not have to explain what they are looking at.
Grounded in tenant data
RAG over each customer's own records and documents plus your product docs, with citations in every answer.
Inline suggestions
Ghost text, smart defaults and next-step hints inside forms and editors, shown only when confidence is high.
Command palette and chat
A side panel, a command bar and contextual buttons, so users reach the copilot in whichever way suits the task.
Actions, not just answers
Typed actions mapped to your existing API, such as creating records, applying filters or changing settings, with a preview and undo.
Permission inheritance
Every retrieval and action runs as the signed-in user, so the copilot can never see or change more than that user can.
Adoption analytics
Track usage, suggestion acceptance, actions completed and feature discovery per plan and per account.
Graceful fallbacks
When the copilot is unsure, it says so, links to the right help article or hands off to support with context.
The copilot reuses your existing APIs and permission model, so it stays in sync with the product as it changes.
The surfaces where users meet the copilot.
Gathers what the copilot needs to know about this moment.
Decides how to answer or which action to propose.
Your existing systems, called with the user's own token.
Keeps the copilot safe and shows whether it helps.
In-product beta
We start with answers grounded in your docs and tenant data, then add actions with previews once the team trusts it. Each step ships behind a feature flag.
Scope Your CopilotEvery copilot reuses the product's own APIs and permissions. What changes is the work users are trying to finish.
Copilots that help customers use the product they already pay for.
Policy answers and form filling inside HR systems, scoped to each employee.
Merchant tools that write listings, explain sales and set up promotions.
Course and admin copilots for instructors and learners inside the platform.
Campaign and content copilots that work from the brand guide and the data.
Technician copilots that read diagnostics and suggest the next step on site.
Your copilot acts inside your customers' accounts. These controls keep it inside the lines.
Retrieval filters and API calls use the signed-in user's token, so role-based and row-level access rules apply to the copilot too.
Write actions show a preview of exactly what will change and wait for the user to confirm, with undo where your API supports it.
Indexes, caches and conversation history are partitioned per tenant and tested with cross-tenant probes before every release.
Customer admins can turn the copilot on or off, limit which actions it can take and export its activity log.
Rated 4.9/5 on average across the platforms clients review us on.
Clutch5.0
GoodFirms5.0I had the pleasure of working with Sajal Tech on a travel website, and it was an incredible experience from start to finish. They demonstrated professionalism, clear understanding of requirements, and excellent communication throughout.
Copilots need fast responses for inline help and strong reasoning for actions, so most use more than one model.
We launch a narrow copilot to a beta group, measure adoption, then add actions and surfaces.
1 week
Study where users get stuck, pick the first jobs for the copilot and list the API actions it needs.
2 to 3 weeks
A context-aware copilot that answers questions from product and tenant data, released to internal users and friendly customers.
3 to 4 weeks
Add confirmed actions, inline suggestions and admin controls, then roll out by plan or account.
Ongoing
Cover more screens, tune suggestions from acceptance data and add actions as your product ships new features.
Indicative starting prices. You get a fixed quote after a free scoping call, with a model cost estimate per active user.
A help assistant in your web app that answers from your docs and cites its source, with handoff to your team.
From
$1,500
1 week
A copilot that reads tenant data and takes confirmed actions.
From
$4,000
3 to 5 weeks
A copilot across your whole product with inline help and admin controls.
From
$25,000
2 to 4 months
Still deciding? A 30-minute call usually answers the rest.
Ask Us DirectlyA website chatbot answers general questions for visitors. A copilot lives inside the signed-in product, knows what the user is doing and who they are, and can take actions in their account. It is part of the product experience rather than a support channel.
No. It calls your APIs with the user's own session or token, and retrieval is filtered by the same roles and row-level rules your product already enforces. We test this with cross-role and cross-tenant cases before release.
Anything your API supports and you choose to expose: creating records, applying filters, changing settings, drafting content or starting a workflow. Write actions show a preview and need user confirmation.
Usually very little. We reuse your existing API and permission service, add a small copilot service and register the actions it may call. If your API has gaps, we add focused endpoints.
It depends on how often users call it and which models answer. We route simple requests to fast, low-cost models, cache common answers and measure cost per active user during the beta so you can price the feature.
Many SaaS companies include basic help in every plan and charge for action features or higher usage as an add-on. We build metering so you can test either model once you see adoption data.
We track adoption, suggestion acceptance, actions completed, ticket deflection and retention for accounts that use it. Answer quality is scored on an eval set built from real user questions.
We build copilot UIs in React, Next.js and Angular, and can ship a web component for older frontends. The look and feel matches your design system.
An answering beta usually ships in 2 to 3 weeks after a one-week journey review. Adding confirmed actions, inline suggestions and admin controls takes another 3 to 4 weeks.
Book a free strategy call and leave with a clear plan and estimate. No commitment.