KServe Company Research Skill
This skill produces a comprehensive BD intelligence report on a prospect company so KServe's business development team can reach out to the right people with the right message. The output is a structured chat summary with verified sources for every data point.
Compatible with: Claude.ai · Claude Code · Cowork · OpenCode · Codex · Any AI agent platform
About KServe
KServe is an AI-powered Business Process Outsourcing (BPO) company headquartered in Thane, Maharashtra, India. KServe helps businesses grow and operate more efficiently by taking over key business functions — powered by integrated AI technology that delivers faster turnaround, higher accuracy, and better outcomes than traditional BPO.
Services
| Service | What KServe does |
|---|
| Lead Generation | Identifies and sources potential customers for the client's sales pipeline |
| Lead Qualification | Evaluates leads to determine fit, intent, and readiness to buy — so the client's sales team focuses only on high-value prospects |
| Customer Onboarding | Manages the end-to-end process of welcoming and activating new customers on behalf of the client |
| Staff Augmentation | Provides trained, dedicated staff who work as an extension of the client's own team — without the overhead of in-house hiring |
| Customer Service | Handles inbound and outbound customer interactions across voice, chat, email, and other channels |
| Back-Office Operations | Takes over internal processing tasks — data entry, documentation, verification, and admin workflows |
| Collection | Manages payment follow-ups, outstanding dues, and recovery processes on behalf of the client |
| Market Research | Gathers competitive intelligence, customer insights, and market data to support the client's business decisions |
All services can be augmented with KServe's AI technology — enabling automation, smarter routing, predictive insights, and higher throughput at lower cost.
Target Industries
BFSI · NBFC · Banking & Securities · Insurance · eCommerce · Education / EdTech · Automobile · Energy & Utilities · Healthcare · Media & Entertainment · Real Estate · Retail · Manufacturing · Tours & Travel · Hospitality · Agriculture · Immigration · Accounting · Fintech · Food & Beverages · Supply Chain Management · Logistics
Platform Execution Mode
Detect your execution mode before starting. Apply it consistently throughout.
| Mode | When to use | Platforms |
|---|
| PARALLEL | You can spawn independent subagents that run simultaneously | Claude Code ( tool) · OpenCode () · Codex agent () · Any multi-agent platform |
| SEQUENTIAL | Single-thread only — one step at a time | Claude.ai · Cowork · Codex chat · Any single-thread assistant |
If unsure, default to SEQUENTIAL — it is always safe, just slower.
PARALLEL: Spawn Workers 2–15 all at once after user confirms. Each Worker runs its own Checker loop. Orchestrator assembles the report once all Workers complete. Note: Step 10 (KServe Fit) depends on Steps 2–9 — spawn it last.
SEQUENTIAL: Run Steps 2–15 in order. Complete each Worker → Checker loop before advancing. Assemble and present the full report after Step 15.
Tool naming across platforms:
- Web search: , , , , or equivalent
- File write: , , , or equivalent
- Subagents: , , , or platform equivalent
Research Flow
Phase 1 — Verification (always first, on every platform)
Search the web for the company. Present the user with:
- Company name (as found)
- Website URL
- Registered / primary address
- Brief one-line description
Stop and wait for the user to confirm this is the right company before proceeding. If the user provided a website or address, use it to narrow the search.
Example:
I found the following. Is this the company you mean?
**Name:** Reliance Retail Ltd.
**Website:** https://www.relianceretail.com
**Address:** 3rd Floor, Court House, Lokmanya Bal Gangadhar Tilak Marg, Mumbai – 400002
**About:** India's largest retail chain across grocery, fashion, and electronics.
Please confirm and I'll run the full research.
Phase 2 — Full Research (after user confirms)
Run all 14 research steps (Steps 2–15) using the execution mode detected above. Each step follows the Worker → Checker → Orchestrator pattern:
- Worker gathers data for that step using available web/search tools
- Checker validates the output against the five criteria (see Checker Instructions)
- If anything fails, Checker returns specific feedback to Worker — loop repeats
- Once approved, output passes to the Orchestrator
- Orchestrator assembles the final report once all steps are complete
Core Research Principles
These principles apply to every step and every platform. Read them before executing any step.
Recency first. Prioritize sources from the last 12 months. If only older data is available, use it but note in report:
⚠️ Most recent available: [FY/date]. Newer data may not yet be public.
Every data point needs a source. Never present a fact without a URL or document reference. If something cannot be sourced, write "Not publicly available" — do not guess.
MCA is ground truth for Indian companies. For these fields, always use MCA (mca.gov.in) as the primary source:
- Incorporation date (Step 5)
- Current directors (Step 6)
- Registered address (Step 4)
- Financial filings / turnover (Step 3)
Tofler, Zauba Corp, and similar aggregators pull from MCA and are acceptable secondary sources.
BD framing throughout. Every section must be written with the lens of: "How does this help KServe win this account?" — not raw data, but insight.
Graceful degradation. If a tool or data source is unavailable, note it clearly in that section and move on. Never halt the entire report because one step hit a wall.
Source Priority Reference
Use this table for every step. Each step lists which sources to try in order of preference.
| Step | Primary | Secondary | Fallback |
|---|
| 2 — Line of Business | Company website (About page) | LinkedIn company page | News articles · Industry directories |
| 3 — Turnover | MCA filings (AOC-4 Annual Return, MGT-7 Board Report) | Tofler · Zauba Corp | News articles · Annual reports |
| 4 — Head Office | MCA registered address | Company website | Google Maps Business listing |
| 5 — Years in Existence | MCA company master data | Company website (Our Story / About) | LinkedIn Founded year · Wikipedia |
| 6 — Directors | MCA director listing | Tofler | Company website (Leadership) · LinkedIn |
| 7 — Branches | Company website | Google Maps | News · LinkedIn (employees by location) |
| 8 — Reviews | Google Business · Glassdoor · AmbitionBox (see step for industry table) | Trustpilot · Justdial · IndiaMart | App Store / Play Store reviews |
| 9 — Rating | Synthesized from Step 8 output | — | — |
| 10 — KServe Fit | Synthesized from Steps 2–9 output | — | — |
| 11 — Customer Care | Company website | Google Business · Justdial | App Store / Play Store listing |
| 12 — Social Media | Direct platform search (LinkedIn, Instagram, Facebook, X, YouTube) | Social Blade (trends) | Company website social links |
| 13 — Tracxn | Tracxn.com | Crunchbase (fallback if Tracxn locked) | — |
| 14 — M&A | News (last 12 months) | Tracxn · Crunchbase · MCA filings | ET · Mint · Business Standard |
| 15 — BD Briefing | Synthesized from Steps 2–14 output — no new searches | — | — |
Research Steps (Steps 2–15)
Step 2 — Line of Business
Find: industry, core products/services, business model (B2B / B2C / B2G), key customer segments.
Step 3 — Turnover (₹ Crores)
Find annual revenue/turnover in Indian Rupees (Crores). Always include the financial year (e.g., FY2023-24).
For Indian-registered companies: use MCA annual filings → Tofler/Zauba → news.
For non-Indian companies or Indian subsidiaries of foreign entities: report in original currency, convert to INR at filing-date exchange rate, and note in report:
Revenue in [currency]; converted to INR at [rate] as of [date].
If not publicly available: write "Private company — turnover not publicly disclosed."
Step 4 — Head Office Location
Find the primary registered office address. Cross-reference MCA registered address against company website — they sometimes differ. If different, report both:
Registered (MCA): [address] | Current operations (website): [address]
Step 5 — Years in Existence
Find the incorporation / founding year. Calculate age from today.
Step 6 — Directors
Pull current directors from MCA. For each: Full name · Designation (MD, Director, Independent Director, etc.) · DIN (Director Identification Number).
For BD outreach, identify for BD outreach: directors likely to be decision-makers for outsourcing (MD, COO, CFO, VP Operations).
Step 7 — Branches & Offices
Find: total number of offices/branches/locations · key cities/states · any international presence.
Step 8 — Reviews & Reputation (Last 12 Months)
Search for reviews from the last 12 months on platforms relevant to the company type:
| Company type | Platforms to check |
|---|
| Consumer brand / eCommerce | Google Business · Trustpilot · Flipkart · Amazon · Myntra |
| Employer brand | AmbitionBox · Glassdoor · Indeed |
| B2B / General | Google Business · Justdial · IndiaMart |
| Finance / Insurance | Google Business · consumer forums |
Synthesize into:
- Top 5 Positives — recurring themes across multiple reviews (note frequency)
- Top 5 Negatives — recurring pain points (these are BD opportunities for KServe)
- Platforms checked — list each with review count and date range
If less than 12 months of reviews exist, include older reviews and note in report:
⚠️ Full 12-month data unavailable; includes reviews from [date range].
Step 9 — Overall Business Rating (out of 10)
Assign a synthesized reputation score — NOT an average of star ratings. Base it on the review themes from Step 8.
Rating anchors:
| Score | Label | Criteria |
|---|
| 9–10 | Excellent | Few complaints, strong positive trends, company actively responds to feedback |
| 7–8 | Good | Mostly positive, some recurring but minor issues |
| 5–6 | Fair | Mixed reviews, notable pain points alongside positives |
| 3–4 | Poor | Majority negative, serious issues (e.g., unfulfilled orders, unresolved complaints), low responsiveness |
| 1–2 | Very Poor | Severe, consistent failures across multiple platforms |
Provide a 2–3 sentence rationale. Note: a lower score often signals more BPO opportunity for KServe.
Step 10 — KServe Services Fit
Depends on: Steps 2–9 (LoB, size, reviews, directors). In PARALLEL mode, run this step last — after all other workers complete.
Based on the full research picture, recommend 3–5 services (not all 8) with explicit fit levels:
- ⭐ HIGH FIT — service directly addresses a visible pain point found in reviews or news
- ✅ MEDIUM FIT — service aligns with company strategy, size, or industry norms
Omit LOW FIT services entirely — only include what is genuinely relevant.
Format each as:
[Service] — [Fit level] — [Specific evidence from research]
Example:
Customer Service ⭐ HIGH FIT
Glassdoor reviews cite "2-hour wait times" and "unresponsive support" — a direct signal
that in-house customer ops are stretched. KServe's AI-powered CX management addresses this.
Lead Generation ✅ MEDIUM FIT
Company is expanding into 3 new cities (per recent news). Qualified outbound lead gen
could accelerate market entry without growing headcount.
Step 11 — Customer Care Number
Find their publicly listed customer support / helpline number.
BD insight: presence of a published number signals a formal support structure. Absence may indicate underdeveloped customer ops — a potential KServe entry point. If no number is found, note in report: "No published support number found."
Step 12 — Social Media Followers
Pull current follower counts: LinkedIn · Instagram · Facebook · Twitter/X · YouTube (if applicable).
Engagement signal (check the main platform — LinkedIn for B2B):
- Review last 5–10 posts
- Note if engagement rate appears low (<2% likes+comments/followers) or posting frequency is sparse (<1×/month)
- Flag low engagement in report as:
Low engagement — [platform]: [observation]
Step 13 — Tracxn Profile
Search Tracxn.com for the company. Report: Tracxn Score (0–100 scale, if available) · category/sector tags · funding stage · investors · notable badges.
If company is not on Tracxn (common for traditional/non-VC companies): note in report
Not on Tracxn — likely private/bootstrapped.
and check Crunchbase as fallback.
If Tracxn profile requires a paid subscription to view detail: note in report
Tracxn profile exists but detail is gated.
Step 14 — Acquisitions & M&A Activity
Search for any recent (last 12 months preferred): acquisitions · being acquired · mergers · major investment rounds · PE/VC backing changes.
BD signals:
- Being acquired → may freeze vendor decisions (note in report)
- Fresh funding raised → likely expanding, open to outsourcing (highlight as trigger signal for Step 15)
Step 15 — BD Intelligence Briefing
Most important step. Synthesize findings from Steps 2–14 into actionable outreach intel. Do not run new web searches — use only what was gathered in prior steps.
A. Things to Know Before Reaching Out (3–5 bullet points)
Current strategic focus · key decision-makers · recent challenges visible in research.
B. Conversation Starters (3–5 specific, recent hooks)
Based on actual events found in research (expansion, funding, product launch, leadership hire, negative reviews).
Format: "[Company] recently [event] — we've helped similar companies with [KServe service] in situations like this."
C. Trigger Signals — Why Reach Out Now (top 2–3 only)
Select the most compelling from:
- Rapid hiring (scaling pain) · Geographic expansion · New product/service launch
- Negative reviews spiking · Funding round closed · Leadership change
D. Potential Objections & Responses (2–3 only)
Based on company profile, anticipate likely pushbacks and provide a suggested KServe response for each.
Output Format
Present the final report using this template:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🏢 KSERVE BD RESEARCH REPORT
Company: [Name]
Research Date: [Date]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✅ VERIFICATION
[Website | Address | Confirmed by user]
📋 LINE OF BUSINESS
[Summary]
Source(s): [URL] | [URL]
💰 TURNOVER
[₹ X Crores | FY XXXX-XX]
Source(s): [URL]
📍 HEAD OFFICE
[Address]
Source(s): [URL]
📅 YEARS IN EXISTENCE
[Founded XXXX | X years old]
Source(s): [URL]
👔 DIRECTORS
[Name — Designation — DIN]
[Name — Designation — DIN]
Source(s): [MCA URL]
🗺️ BRANCHES & OFFICES
[X locations | Key cities]
Source(s): [URL]
⭐ REVIEWS & REPUTATION (Last 12 months)
Top 5 Positives:
1. ...
Top 5 Negatives:
1. ...
Platforms checked: [Platform — X reviews — date range — URL]
🎯 OVERALL RATING: X/10 — [Label]
[2–3 sentence rationale]
🤝 KSERVE FIT ASSESSMENT
[Service — Fit level — Evidence]
📞 CUSTOMER CARE NUMBER
[Number or "Not published"] | Source(s): [URL]
📱 SOCIAL MEDIA FOLLOWERS
LinkedIn: X | Instagram: X | Facebook: X | Twitter/X: X | YouTube: X
Source(s): [URLs]
📊 TRACXN PROFILE
[Score / Not listed / Gated]
Source(s): [URL]
🔀 M&A & FUNDING ACTIVITY
[Summary or "No recent M&A activity found"]
Source(s): [URL]
🧠 BD INTELLIGENCE BRIEFING
Things to Know:
• ...
Conversation Starters:
• ...
Trigger Signals:
• ...
Potential Objections:
• [Objection] → [Suggested response]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📝 DATA QUALITY
Confidence: High (MCA-verified) / Medium (aggregators + news) / Low (partial data)
Data age: [All within 12 months / Mixed — oldest source: date]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Multi-Agent Architecture
PARALLEL MODE
User confirms company (Step 1)
│
▼
┌─────────────────────────────────────────┐
│ SPAWN SIMULTANEOUSLY (Steps 2–9, 11–14) │
│ Worker-2 Worker-3 Worker-4 ... │
│ Worker-5 Worker-6 Worker-7 ... │
│ Worker-8 Worker-9 Worker-11 ... │
│ Worker-12 Worker-13 Worker-14 │
│ (Step 10 spawns last — needs 2–9) │
└─────────────────────────────────────────┘
│ (each worker ↔ checker loop)
▼
┌─────────────────────────────────────────┐
│ CHECKER (per worker) │
│ Validates: source · credibility · │
│ recency · accuracy · completeness │
│ Returns to worker if any fail │
└─────────────────────────────────────────┘
│ (all approved outputs)
▼
┌─────────────────────────────────────────┐
│ ORCHESTRATOR │
│ Assembles all 14 approved sections │
│ Validates completeness of report │
│ Renders final BD Research Report │
└─────────────────────────────────────────┘
SEQUENTIAL MODE
User confirms company (Step 1)
│
┌────▼────┐
│ Step 2 │ Worker → Checker validates → approved ✓
└────┬────┘
┌────▼────┐
│ Step 3 │ Worker → Checker validates → approved ✓
└────┬────┘
...
┌────▼─────┐
│ Step 15 │ Worker → Checker validates → approved ✓
└────┬─────┘
│
▼
Orchestrator assembles and presents final report
Checker Instructions
When validating any Worker output, apply all five criteria:
- Source present? Every fact must have a URL or named document. No source → send back.
- Source credible? Prefer official sources (MCA, company website, major publications) over anonymous forums or low-quality aggregators.
- Recency? Is the data from the last 12 months? If older, is it noted in the report with a ⚠️?
- Accurate? Does the data make internal sense? (e.g., a 2-year-old company cannot have 50 years of history)
- Complete? Did the Worker answer everything the step requires, or are there gaps?
If any criterion fails, return to Worker with specific, actionable feedback:
"The turnover figure has no source — find the MCA filing or a news article citing the exact revenue figure."
Max retries: 2. If the Worker cannot satisfy all criteria after 2 attempts, approve with this note in the report:
⚠️ [Field]: Best available data — [brief reason data is incomplete or unavailable]
Conflicting sources: If sources disagree (e.g., MCA address differs from company website), defer to MCA and report both:
Registered (MCA): [value] | Current (website): [value]
Only approve when all five criteria are met (or a ⚠️ note is included for genuinely unavailable data).
Orchestrator Instructions
After all 14 Workers complete and each Checker has approved:
- Assemble all approved sections into the Output Format template in order
- Validate: no field is blank, pending, or "TBD" without a "Not publicly available" statement or a ⚠️ flag
- If any section is missing or incomplete, return to that step's Checker with a re-request before rendering
- Render the final report for presentation to the user