Skimle for consultants & investors
Spend 80% of your time on insights, not organising data
Consulting and investment work is won or lost on the quality of qualitative analysis — expert calls, management interviews, data room documents, market research. The tools for quantitative work are solid. The qualitative side is still being hacked together with Word docs and Excel trackers.
Skimle gives consulting teams and investors the same rigour they apply to financial modelling, but for text. Upload expert transcripts, data room documents, or research reports. Skimle reads everything, surfaces themes, flags outliers, and links every finding to a verbatim quote — so you can defend your recommendation in a steering committee without breaking a sweat.
Analysis that matches client expectations for depth and speed
What took weeks of analyst time takes hours with Skimle — without sacrificing the rigour partners and investment committees demand. Skimle was built by a former McKinsey Partner who conducted over 1,000 client interviews and knows exactly where qualitative analysis breaks down under project pressure.
- Every expert call, data room document, and market report in one project workspace
- AI identifies themes, consensus views, outlier opinions, and red flags in minutes
- Full traceability — every finding links to a specific verbatim quote
- Works in 100+ languages across global projects and multi-country research
- Client-ready exports in Word, PowerPoint, and Excel
- Data stays in the EU — GDPR-compliant with Data Processing Agreements available
FROM 40 CALLS TO A DEFENSIBLE SYNTHESIS
Distil insights from stakeholder, expert and client calls
You have done 40 expert network calls, 20 client discussions and 10 internal expert problem solving sessions, and the synthesis deck is due Monday. How do you extract insights from 1000s of pages without just skimming and hoping you caught the important parts? Skimle reads every document, builds a bottom-up theme structure of consensus views, contradictions, and outlier opinions, and links every finding to the exact quote that supports it.
How it works
- 1. Upload all documents
Export transcripts from any expert network platform and other source.. Mix call notes, interview transcripts, and written submissions in one project.
- 2. Orient around your hypothesis
Describe what you are looking for in plain language, for example the top branches of your issue tree. Skimle structures the analysis around what you are trying to validate or disprove by automatically creating further sub-categories and finding the facts for each from the uploaded documents.
- 3. Review consensus and outlier views
Skimle surfaces themes across all transcripts, flags where experts agree, and highlights the dissenting views that carry analytical weight.
- 4. Verify every finding
Click any theme to see the supporting quotes and which expert said what. Partners can review the logic directly — no black boxes or “computer said so” moments.
- 5. Export the synthesis
Generate a structured synthesis document with representative quotes and appendices — ready for the deck or the client deliverable.
NEVER MISS THE RED FLAG ON PAGE 67 OF DOCUMENT 42
Analyse DD interviews, management presentations, and data room documents
Due diligence means reviewing 1,000 documents in two weeks — you cannot read everything, so you sample, and risk missing the red flag buried on page 67 of document 42. Skimle reads the entire data room, not a sample: it flags non-standard clauses, surfaces concentration risks, and maps management claims against interview data, with every finding linked to the exact document and page.
How it works
- 1. Upload the full document set
Drag in PDFs, Word documents, presentations, and spreadsheet exports — up to 1,000 documents per project. No need to sort or pre-process.
- 2. Orient around your deal or issue tree
Frame the analysis around your investment thesis or diligence framework. Skimle structures findings to match your deal logic, not generic categories.
- 3. Surface red flags and validate claims
Cross-reference what management says against what customer interviews and contracts show. Contradictions surface automatically.
- 4. Full traceability for partner review
Every finding links to its source document and exact passage. Partners can drill in, challenge assumptions, and review evidence directly.
- 5. Export the diligence report
Generate a structured report with risk categories, supporting quotes, and document references — ready for the investment committee.
ONE UNIFIED VIEW ACROSS ALL WORKSTREAMS AND MARKETS
Synthesise primary research across geographies or project workstreams
Multi-country projects produce research in parallel workstreams — market analysis in German, customer interviews in French, regulatory filings in English — and nobody gets a consistent cross-market picture until the final read-out, when it is too late to fill gaps. Skimle analyses all workstreams and languages in a single project, building one unified theme structure across the full dataset rather than reconciling different analysts' interpretations.
How it works
- 1. Upload research across all workstreams
Mix languages, formats, and sources freely in one project. Tag documents by geography or workstream using metadata variables.
- 2. Build a unified theme structure
Skimle applies consistent coding across all documents, regardless of language — so German and French findings map to the same theme hierarchy as English.
- 3. Compare findings across markets
See which themes are consistent globally and which vary by market or workstream. Identify contradictions between what different sources show.
- 4. Query specific topics across the dataset
Ask targeted questions across the full corpus — “What did CFOs say about pricing pressure?” or “Where do regulatory risks cluster?” — and get sourced answers in seconds.
- 5. Deliver a consolidated synthesis
Export one unified report across all workstreams — with market-by-market breakdowns and cross-market patterns clearly separated.
FAQ
Frequently asked questions
- Will clients accept AI-assisted analysis?
- Yes — if you position it correctly. Clients care about insight quality and speed, not your tools. Frame it as AI-assisted human analysis: AI handles data organisation, you provide strategic interpretation. Skimle's full traceability means you can defend every recommendation with evidence, which is a stronger position than traditional manual synthesis where the coding logic is invisible.
- Can we use this for confidential client data?
- Yes. Data is processed securely, stored in the EU, and never used to train AI models. Skimle provides Data Processing Agreements for institutional clients and can accommodate most IT security requirements, including single-tenant cloud deployments for firms with stricter data sovereignty needs.
- How does this work with expert network transcripts from GLG, AlphaSights, or Tegus?
- Export transcripts from any expert network platform and upload directly to Skimle. It handles any transcript format and allows you to centralise all expert call analysis in one project, alongside data room documents and market research, rather than working across fragmented platform-specific tools.
- What if partners need to review the analysis?
- Skimle maintains a full audit trail. Partners can see exactly which sources support which conclusions, review coding logic, and drill into specific topics. The transparency makes partner review faster — they can navigate the full evidence base directly rather than asking analysts to pull supporting quotes on demand.
- Does this replace junior analysts?
- No — it makes them more effective. Junior analysts spend less time on mechanical tasks (organising quotes, building trackers) and more time on value-add work (client interviews, analysis, recommendations). They can handle more complex projects earlier in their career, and quality is more consistent across seniority levels.
- Can we run multiple workstreams in the same project?
- Yes. You can tag documents by workstream, geography, source type, or any other variable, and then filter themes and patterns by those tags. A market entry project with four country workstreams can be managed in one Skimle project, with both workstream-level and cross-market views available.
- How much does Skimle cost compared to hiring research support?
- A typical due diligence project that takes 300 analyst hours manually takes around 48 hours with Skimle. Individual plans start at €40 per month. Organisational and enterprise plans with custom volumes and team features are available — contact us to discuss options for consulting firms and PE shops.
Choosing your analysis approach
Skimle vs. other consulting analysis approaches
When evaluating analysis methods for consulting projects, consider project economics and competitive positioning.
| Manual Excel / Word | Ad hoc AI ChatGPT / Claude | Outsourced team | Skimle | |
|---|---|---|---|---|
| Speed | Slow (2–3 weeks) | Fast (hours) | Medium (1+ week) | Fast (1–2 days) |
| Quality / rigour | Good (if time allows) | Poor — no traceability | Excellent | Excellent |
| Handles complexity | Breaks down at scale | Limited context | Yes (expensive) | Yes |
| Multi-source integration | Manual | Limited | Manual | Built-in |
| Client-ready outputs | Manual formatting | Needs heavy editing | Yes | Automated |
| Defend recommendations | Manual documentation | Difficult | Good | Full traceability |
| Cost (typical project) | Analyst time (€5k–15k) | ~€100 | €10k–25k | €100–500 |
| Scales across projects | No knowledge retention | No | High staff costs | Yes |
| Verdict | Best only for very small projects where personal synthesis is faster than setup time. | Fine for quick drafts — but partners will ask “How do you know this?” and you won't have a good answer. | When you have deep bench capacity, no time pressure, and project economics support the analyst hours. | 15+ expert interviews, large data rooms, tight deadlines, or when you need to defend recommendations with a full evidence trail. |
About Skimle
Built for professionals, by professionals
Skimle is based in Finland and co-founded by a former McKinsey Partner and a Professor of Strategy at Aalto University — people who have spent careers doing qualitative analysis under real professional pressure. We built Skimle because we needed it ourselves.
We are trusted by Finnish government ministries, over 30 universities, dozens of consulting and market research firms, and large companies. All data is stored within the EU and processed according to our strict GDPR policy and terms of service.
For consulting firms and PE shops interested in team plans, enterprise licensing, or white-label arrangements, get in touch. We are happy to discuss firm-wide agreements and custom deployments.