── AI copilot development services ──

Copilots inside your own tools.

Assistants built into your CRM, helpdesk and internal tools that draft, find and fill in, with the person in charge approving every change.

Start a project →

Free 30-minute scoping call. Written estimate within 5 working days.

Inside your tools · Cited suggestions · You approve · Your cloud

Illustrative interface. Values are sample data.

0+.AI systems in production
0.Days to first deploy · median
0.0%.Uptime · managed inference · 12 mo
0.0×.Cost reduction · fine-tuned vs API · median

* Sample figures for layout review. Replace with audited numbers from engagement reports before launch.

── 01 · AI copilot development services ──

Six services, one copilot your team uses.

AI copilot development is building assistants that work inside the software people already use, suggesting the next step while the person stays in charge.

  1. 01

    Copilot consulting.

    Which roles and tasks a copilot should help with first, and how you'll measure it.

    Deliverable · Copilot opportunity map
  2. 02

    Copilot UX design.

    Where suggestions appear, how people accept or edit them, and how the copilot explains itself.

    Deliverable · Interaction design
  3. 03

    Custom copilot development.

    Retrieval, actions and prompts built around one team's daily work.

    Deliverable · Production copilot
  4. 04

    Copilot integration.

    Embedded in your CRM, helpdesk, intranet, IDE or product through their APIs.

    Deliverable · Embedded copilot
  5. 05

    Training and fine-tuning.

    Models tuned on your examples when a general model doesn't match your tone or format.

    Deliverable · Tuned model
  6. 06

    Support and improvement.

    Acceptance, edits and feedback reviewed monthly to improve suggestions.

    Deliverable · Monthly adoption report
── 02 · Where copilots live ──

Six places copilots earn their keep.

A copilot works best inside the tool where the work already happens, not in another tab.

CRM copilot.

Next steps, call summaries and follow-up drafts on every account and deal.

Lives in · Salesforce, HubSpot, Dynamics

Helpdesk copilot.

Suggested replies with sources, ticket summaries and one-click macros for agents.

Lives in · Zendesk, ServiceNow, Intercom

Document copilot.

Clause checks, summaries and redlines inside the documents your team already edits.

Lives in · Word, Google Docs, contract tools

Analytics copilot.

Questions in plain language turned into charts and numbers from your own data.

Lives in · BI tools, internal dashboards

Engineering copilot.

Code suggestions, reviews and test drafts that follow your team's conventions.

Lives in · IDE, code review, CI

Field-service copilot.

Step-by-step guidance from manuals and past jobs, on the technician's phone.

Lives in · mobile apps, tablets

* Previews are illustrative. Product names belong to their owners; no partnership is implied.

── 03 · Features ──

Built around the person, not the model.

Sixteen features in four groups. Each one is tested with the people who will use it.

— Understanding context —

  • Context from the current record
  • Your documents, with citations
  • Team conventions
  • Personal preferences

— Helping with the task —

  • Drafts and summaries
  • Form filling
  • Next best step
  • Search across systems

— Working together —

  • Accept, edit or dismiss
  • An explanation for every suggestion
  • Feedback that improves it
  • Hand-off to a colleague

— Measuring value —

  • Acceptance rate
  • Time saved per task
  • Edit rate
  • Cost per active user
── 04 · Measuring adoption ──

Adoption you can measure.

A copilot nobody accepts is a cost, not a feature. We report what happened to every suggestion.

  • Acceptance and edit rates per team and per task
  • Time per task before and after, on the same work
  • Dismissal reasons, fed back into prompts and retrieval
  • Cost per active user, against the time saved
— What happened to each suggestion · 30 days —
Suggestions shown · 30 days12,400
Read or expanded79%
Accepted as is43%
Accepted with edits25%
Dismissed32%
Illustrative sample data.
── 05 · Trust and control ──

The person stays in charge.

A copilot suggests; people decide. These controls make that true in practice, not just in the pitch.

  1. 01

    Suggest, don't act.

    Nothing is sent, saved or changed until a person accepts it, unless you've agreed otherwise for a task.

  2. 02

    Explanations and sources.

    Every suggestion shows why it was made and which records or documents it drew on.

  3. 03

    Same permissions as the user.

    The copilot only sees what the person using it can see, enforced by your identity provider.

  4. 04

    Data stays private.

    Built in your cloud, with providers set to zero retention. Your data never trains a public model.

  5. 05

    Compliance support.

    Built to support GDPR, HIPAA and SOC 2 controls, with your security team and counsel signing off.

Illustrative interface. Values are sample data.

— Case studies —

The first cohort is being written.

Named case studies publish here with the client's sign-off, real numbers and the honest limits. Want to be one of them?

Talk to us →
── 06 · Industries ──

Copilots for your industry.

Every industry has its own tools and rules. Suggest-first design, evaluation and adoption tracking stay the same.

Mobility.

Dispatch, ETA and rider-support agents for ride-hailing and fleet platforms.

ETA models · Demand forecasting · Support agents

Logistics.

Route optimisation, document extraction and exception handling across the shipment lifecycle.

Route optimisation · Document AI · Exception triage

Finance.

KYC document extraction, fraud signals and customer assistants that stay inside compliance rules.

KYC extraction · Fraud signals · Compliance copilots

Real estate.

Listing enrichment, valuation models and lead-qualifying agents for brokerages and proptech.

Valuation · Listing enrichment · Lead agents

Retail / Manufacturing.

Demand forecasting, visual inspection and inventory copilots on the shop and factory floor.

Forecasting · Visual inspection · Inventory copilots

eCommerce / Consumer goods.

Product search, personalisation and post-purchase support agents that cite the order.

Semantic search · Personalisation · Support agents

Travel.

Itinerary assistants, dynamic pricing and disruption-handling agents for OTAs and operators.

Itinerary agents · Pricing · Disruption handling
— Not listed? —

Let's discuss your industry.

If the data is messy and the stakes are real, the method still applies. Bring the workflow; we'll bring the evaluation set.

Start a project →
── 07 · Development process ──

From shadowing users to daily use.

Discovery starts by watching the work. The evaluation set comes from real tasks, and early users shape every release.

  1. 01 Discovery · week 1

    Workflow and data audit.

    We map the process, pull a sample of real data, and check what is usable, missing or sensitive.

  2. 02 Discovery · week 2

    Evaluation set.

    We build the test set from your real examples, so “done” has a number before any product code exists.

  3. 03 Build · sprint 1

    Architecture and prototype.

    Model choice, retrieval design and integration plan, proven against the eval set.

  4. 04 Build · every Friday

    Build in the open.

    Your repository, your cloud. A weekly demo with accuracy, latency and cost on one screen.

  5. 05 Run · go-live

    Deploy.

    A staged rollout behind a feature flag, with runbooks, monitoring and a rollback path.

  6. 06 Run · monthly

    Monitor and improve.

    Drift alerts, model upgrades run through your evals, and a monthly cost and quality review.

── 08 · Technology stack ──

The copilot stack we build on.

Any model, retrieval over your data, and the extension SDKs of the tools your team already uses.

— Models —
  • OpenAI
  • Anthropic
  • Gemini
  • Llama
  • Mistral
  • Qwen
— Agents & orchestration —
  • LangChain
  • Temporal
  • FastAPI
  • Python
— Retrieval & data —
  • pgvector
  • Pinecone
  • Elasticsearch
  • Redis
  • Databricks
  • Snowflake
— Training & serving —
  • PyTorch
  • Hugging Face
  • vLLM
  • NVIDIA TensorRT
  • ONNX
  • OpenCV
— MLOps & observability —
  • MLflow
  • Weights & Biases
  • Grafana
  • Prometheus
  • OpenTelemetry
— Cloud & infrastructure —
  • AWS
  • Google Cloud
  • Azure
  • Kubernetes
  • Terraform
  • Docker

* Tools we build with. No vendor partnership or endorsement is implied.

── 09 · FAQ ──

AI copilot questions, answered.

Short answers here. Longer ones on the scoping call.

— Still have a question? —

Message us on WhatsApp. An engineer replies within one working day.

What is an AI copilot?

An AI copilot is an assistant built into software people already use. It understands the current task, suggests drafts, answers and next steps, and leaves the decision to the person.

How are copilots built into internal tools?

Through the tool's API or extension system: a side panel in the CRM, a button in the helpdesk, a command in Slack or Teams. The copilot reads the current context and writes back only what the person accepts.

How much does an AI copilot cost?

Projects start with a fixed-fee discovery sprint, quoted on the scoping call. The build is priced per milestone, and every quote is written and fixed for its scope.

How long does it take to build a copilot?

After a two-week discovery sprint, a first copilot for one team usually takes four to ten weeks, including a pilot with real users.

How is a copilot different from a chatbot?

A chatbot answers questions in its own window. A copilot works inside the tool you're using, knows the record or document in front of you, and helps complete the task there.

How do you measure whether a copilot is working?

Acceptance and edit rates, time per task before and after, and user feedback, reviewed monthly against the cost per active user.

Can a copilot take actions on its own?

Only where you choose. By default it suggests and a person accepts. For low-risk, repetitive steps you can let it act within set limits, with every action logged.

Is our data safe?

Yes. The copilot runs in your cloud, sees only what each user is allowed to see, and model providers are configured for zero data retention.

── Start a project ──

Bring the workflow. We'll bring the plan.

Three steps from first message to kickoff. No deck, no commitment until you sign.

  1. 01Scoping call30 minutes with an engineer, not a salesperson.
  2. 02Written estimateAn evaluation plan, a timeline and a price within 5 working days.
  3. 03KickoffSign the scope and the discovery sprint starts.

Prefer to message directly? WhatsApp +91 7096010005

— Start a pilot —

This is the one that decides whether a pilot is worth doing.

Nothing is stored on this website — the form opens WhatsApp with the message written out, including the pages you looked at, and you press send.

Fixed fee. Two weeks. Starts with a 30-minute call.

Start a pilot →