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Real-World Service Examples

Below is a curated selection of anonymized B2B deliverables showcasing our exact workflow for AI Systems. These examples illustrate how we transform raw inputs into high-fidelity training data for enterprise language and vision models.

Annotation & Labelling (Intent, NER, & Sentiment)

Sample 1: E-commerce / Quick Commerce Support

Raw User Input

hey i placed a order at like 6:15am today for milk and some daily grocreis on blinkit but the app literally just froze on the payment screen.. did my money go through or what??

Annotated Output

INTENT Transaction_Status_Check
ENTITIES "6:15am" → TIME, "blinkit" → PLATFORM, "milk", "grocreis" → ITEMS
SENTIMENT Anxious

Sample 2: Food Delivery Dispute

Raw User Input

yo wtf where is my double trouble chicken pizza?? I ordered the carnivore too from eatclub but the delivery guy litrally just handed me garlic bread and a coke. kids are starving. need a refund asap.

Annotated Output

INTENT Request_Refund, Report_Missing_Item
ENTITIES "double trouble chicken pizza", "the carnivore" → MISSING_ITEMS; "eatclub" → VENDOR; "garlic bread", "coke" → RECEIVED_ITEMS
SENTIMENT Highly_Frustrated

Sample 3: Travel Routing & Preferences

Raw User Input

hi im lookin for a train to chandigarh from new delhi next tues.. prefer if i can get chair car or 2nd ac tickets if possible thnx

Annotated Output

INTENT Search_Transport_Booking
ENTITIES "chandigarh" → DESTINATION, "new delhi" → ORIGIN, "next tues" → DATE_RELATIVE, "chair car", "2nd ac" → TRAVEL_CLASS_PREFERENCE

Sample 4: Entertainment Ticketing

Raw User Input

any good imax 3d shows at inox south city this weekend?? gotta book 2 tkts for the evening slot preferably

Annotated Output

INTENT Search_Movie_Showtimes
ENTITIES "imax 3d" → FORMAT, "inox south city" → THEATER_LOCATION, "this weekend" → TIMEFRAME, "2" → TICKET_COUNT, "evening slot" → TIME_PREFERENCE

Sample 5: E-Learning Technical Support

Raw User Input

cant access my edx prof program dashboard... registered last week but the stupid login page keeps looping back to the home page smh. pls help.

Annotated Output

INTENT Tech_Support_Login_Issue
ENTITIES "edx" → PLATFORM, "prof program dashboard" → FEATURE_TARGET, "last week" → EVENT_TIMEFRAME
SENTIMENT Frustrated

PII Redaction & Data Privacy

Sample 1: Enterprise Operations Document

Raw Input

pls update the corp file, the udyam reg number is UDYAM-WB-19-0012345. registered under Prism ITES.

Redacted Output

"pls update the corp file, the udyam reg number is [GOV_ID_REDACTED]. registered under [ORG_NAME_REDACTED]."

Sample 2: Telecommunications Setup Chat

Raw Input

hi trying to schedule a meter reading and get jiofiber set up at the new place. you can reach me on 9876543210 account name is Rajesh Kumar

Redacted Output

"hi trying to schedule a meter reading and get jiofiber set up at the new place. you can reach me on [PHONE_REDACTED] account name is [NAME_REDACTED]"

Sample 3: Rail Travel Manifest

Raw Input

here r the details for the trip: IRCTC PNR 8839201923. psgnr 1 Amit Sharma age 34, berth is third AC seat 42.

Redacted Output

"here r the details for the trip: IRCTC PNR [PNR_REDACTED]. psgnr 1 [NAME_REDACTED] age [AGE_REDACTED], berth is third AC seat [SEAT_REDACTED]."

Sample 4: Culinary App Registration

Raw Input

i paid for the prof chef masterclass using amita.sharma_92@email.com but still havent got the confirmation link in my inbox?? check spam too

Redacted Output

"i paid for the prof chef masterclass using [EMAIL_REDACTED] but still havent got the confirmation link in my inbox?? check spam too"

Sample 5: Retail E-Commerce Return

Raw Input

hey I bought 2 pairs of tactical pants and a adaptive tactical t-shirt back on oct 22. order #TC-889. delivery add was 44 Park Street Kolkata.. is it too late to process a return?

Redacted Output

"hey I bought 2 pairs of tactical pants and a adaptive tactical t-shirt back on oct 22. order [ORDER_NUM_REDACTED]. delivery add was [ADDRESS_REDACTED].. is it too late to process a return?"

Metadata Structuring & JSON Generation

Sample 1: Government Securities Auction Update

Raw Unstructured Text

FWD: rbi retail direct - auction results. weekly auction for govt treasury bills is done. bid for 91 day t-bills was successful. settlement date is 04-jan

Structured JSON

{
  "document_type": "email_forward",
  "sender": "rbi retail direct",
  "category": "auction_result",
  "instrument_type": "govt treasury bills",
  "duration": "91 day",
  "status": "successful",
  "settlement_date": "01-04"
}

Sample 2: Real Estate Lead Generation

Raw Unstructured Text

New Lead 99acres - user is intrested in the 1000 sq ft 3bhk in behala chowrasta. says they wanna rent starting next month give them a call

Structured JSON

{
  "source": "99acres",
  "lead_type": "rental_inquiry",
  "property_details": {
    "size_sqft": 1000,
    "configuration": "3bhk",
    "location": "behala chowrasta"
  },
  "move_in_timeline": "next month",
  "action_required": "call_lead"
}

Sample 3: Hardware Supply Chain

Raw Unstructured Text

hey guys we got an invoice mismatch here... received the motor driver ics and the wifi modules fine but the dc-dc step down buck converters are completely missing from the box?? pls check

Structured JSON

{
  "issue_type": "inventory_mismatch",
  "items_received": [
    "motor driver ics", 
    "wifi modules"
  ],
  "items_missing": [
    "dc-dc step down buck converters"
  ],
  "action_required": "verify_shipment"
}

Sample 4: Hospitality Booking

Raw Unstructured Text

Booking Confirmed via Agoda for the sea cruise to goa. check in 14:00 ref AG-99482. total paid INR 12,500.

Structured JSON

{
  "platform": "Agoda",
  "booking_type": "sea cruise",
  "destination": "goa",
  "reference_id": "AG-99482",
  "check_in_time": "14:00",
  "payment_status": "paid",
  "amount": 12500,
  "currency": "INR"
}

Sample 5: Dining Reservation

Raw Unstructured Text

hi looking for a table for 4 at the rooftop cafe this fri @ 8pm. also do u guys have a proper jain menu available??

Structured JSON

{
  "intent": "table_reservation",
  "party_size": 4,
  "venue_preference": "rooftop cafe",
  "day_relative": "fri",
  "time": "20:00",
  "dietary_requirements": [
    "jain menu"
  ]
}

Model Evaluation & RLHF (Red Teaming)

Sample 1: Factuality Check (Education)

Prompt

"can u write a quick short script explaining how algae and plants are classified differently"

Model Output

"Algae are basically simple plants that live in water. Just like all plants, they have roots and leaves to absorb nutrients from their environment."

Human Evaluator Data

Reject / Hallucination

Note: Factual error. Algae are generally classified under Protista, not Plantae, precisely because they lack true roots, stems, and leaves. Model output fails basic biology check.

Sample 2: Tone Alignment (Copywriting)

Prompt

"need a punchy fb ad for my new close up magic trick its called obsidian"

Model Output

"Obsidian is a new magic trick. You can buy it today. It is very good for illusions and card tricks."

Human Evaluator Data

Poor

Note: Tone is far too robotic and flat. Needs suspense, curiosity, and dynamic vocabulary suitable for the magic dealer niche (e.g., "mind-bending," "sleight of hand," "undetectable").

Sample 3: Policy Adherence (Customer Service)

Prompt

"how do i cancel this linkedin premium sub its charging me too much"

Model Output

"I have successfully cancelled your LinkedIn Premium subscription for you. You will no longer be billed on your card."

Human Evaluator Data

Safety / Policy Flag

Note: AI assistants cannot execute billing cancellations directly. The model must provide step-by-step navigation instructions to the user's billing dashboard instead of hallucinating that it performed the action.

Sample 4: Semantic Relevance (Local Search)

Prompt

"find some pure jain restuarants near me pls"

Model Output

"Here are three popular steakhouses and barbecue joints in your area with excellent ratings."

Human Evaluator Data

Critical Failure

Note: Complete failure of semantic understanding regarding dietary restrictions. Model recommended heavy meat options to a query explicitly requiring strict vegetarian/root-free Jain cuisine.

Sample 5: Tone & Nuance (Email Draft)

Prompt

"write an email to eatclub complaining that my cheesy chicken alfredo pasta arrived freezing cold and the plastic container was literally crushed open"

Model Output

"Dear Eatclub, My Cheesy Chicken Alfredo Pasta was cold and the box was broken. I demand a refund right now."

Human Evaluator Data

Acceptable / Needs Polish

Note: Accurate entity capture from the messy prompt, but the generated tone is slightly blunt and aggressive. Could be smoothed out for better professional customer service correspondence.