Data as a Service

Client Background:
A fast-growing B2B SaaS company headquartered in Austin, Texas, offering project management software to mid-market professional services firms. With an aggressive expansion plan targeting 500 new enterprise accounts annually, their sales team needed a scalable, reliable source of verified prospect data.

Challenge:
The company’s internal data team spent 25+ hours per week manually sourcing, cleaning, and de-duplicating prospect lists from LinkedIn, company websites, and industry directories. Data quality was inconsistent — over 35% of contact records had outdated emails or incorrect firmographic details — leading to high bounce rates, poor email deliverability scores, and wasted SDR time on dead leads.

Solution:
Hir Infotech deployed a custom DaaS pipeline delivering 10,000 verified B2B contact records per month, enriched with firmographic data (company size, industry, tech stack, revenue band), direct email addresses, LinkedIn profile URLs, and job titles for C-suite and VP-level decision-makers in target verticals. Data was delivered weekly via REST API directly into their HubSpot CRM with automated deduplication and field mapping.

Results:

• Email bounce rate dropped from 18% to under 2.5%

   

• SDR productivity increased by 42% within 60 days

   

• Pipeline generated from DaaS-enriched outreach grew by $1.2M within the first quarter

   

• Data preparation time reduced by 80%, freeing analysts for strategic work

   

Client Testimonial:
“Hir Infotech transformed how our sales team operates. We went from spending hours chasing bad data to having a clean, verified pipeline delivered directly into HubSpot every week. The ROI was visible within the first month.”
— VP of Sales, B2B SaaS Company, Austin, TX

Client Background:
A mid-market online retailer based in Hamburg, Germany, selling consumer electronics across Amazon.de, Otto, and its own DTC website. The company managed over 8,000 active SKUs and operated in a highly competitive, price-sensitive market segment.

Challenge:
Without a scalable competitive pricing intelligence solution, the company relied on manual spot-checks twice a week — missing intraday price movements from competitors that resulted in lost Buy Box positions, margin erosion, and reactive rather than strategic pricing decisions. They needed real-time, structured competitor price data at scale, compliant with GDPR and German competition law.

Solution:
Hir Infotech deployed an AI-powered DaaS solution monitoring 15 competitor storefronts and marketplace listings in real time — tracking SKU-level pricing, promotional events, stock availability, and seller ratings across Amazon.de, Zalando, MediaMarkt, and three niche electronics portals. Data was delivered every 4 hours via structured JSON to the client’s existing pricing engine and Tableau dashboard.

Results:

• Competitor price coverage increased from 2 checks/week to 6 real-time updates/day

   

• Buy Box win rate improved by 23% within 90 days

   

• Gross margin improved by 4.1 percentage points through data-driven dynamic pricing

   

• Engineering team saved 60+ hours/month previously spent on manual data collection

   

Client Testimonial:
“The quality and frequency of Hir Infotech’s DaaS feed gave our pricing team a genuine edge. We now react to market changes in hours, not days. It’s made a measurable difference to our bottom line.”
— Head of E-Commerce, Consumer Electronics Retailer, Hamburg, Germany

Client Background:
A London-based fintech startup offering AI-powered investment research tools to boutique asset management firms across the UK and continental Europe. Their platform required structured, real-time alternative data feeds to power factor models and sentiment-based trading signals.

Challenge:
Sourcing, cleaning, and normalizing diverse alternative data — earnings call transcripts, regulatory filings, news sentiment, ESG disclosures, and macro indicators — across multiple European markets required building and maintaining 40+ separate data connectors. The engineering burden was consuming 70% of the product team’s capacity, slowing roadmap execution.

Solution:
Hir Infotech provided a consolidated DaaS package covering: normalized financial filing data from SEC (USA) and FCA/Companies House (UK), real-time news sentiment feeds from 200+ sources, structured ESG disclosure data from EU taxonomy-aligned sources, and earnings event data — all delivered via a single REST API with standardized schemas, daily refresh, and a 3-year historical backfill.futuremarketinsights+1

Results:

• Engineering hours spent on data sourcing reduced by 68%

   

• Platform launched 4 new factor models powered by DaaS feeds within 6 months

   

• Client churn in their platform dropped by 31% as data freshness and coverage improved

   

• Time-to-insight for research analysts reduced from 3 days to under 4 hours

   

Client Testimonial:
“Hir Infotech gave us the data infrastructure we couldn’t build ourselves in time. Their DaaS feed quality is exceptional — clean schemas, reliable delivery, and responsive support. It’s become the backbone of our platform.”
— CTO, Fintech Investment Research Platform, London, UK

Client Background:
A Stockholm-based HR technology company providing workforce planning SaaS to large enterprises across Scandinavia. Their product team needed structured labor market data — job postings, skills demand trends, and compensation benchmarks — to power their talent analytics module.

Challenge:
Manually collecting and normalizing job postings data from 30+ job boards across Sweden, Norway, Denmark, and Finland was slow, expensive, and produced inconsistent output. Existing data vendors offered generic, unstructured feeds that required extensive downstream cleaning before they could power the product’s analytics dashboards.

Solution:
Hir Infotech delivered a custom DaaS solution aggregating and normalizing 50,000+ new job postings per week from Indeed, LinkedIn, Glassdoor, and regional Nordic job boards (Finn.no, Jobindex.dk, Monster.se). Each record was enriched with standardized skill taxonomy mapping, seniority classification, salary range normalization, and employer firmographic data — delivered weekly via API in a schema ready for direct database ingestion.

Results:

• Job postings data coverage expanded from 6 to 30+ sources without adding engineering headcount

   

• Product analytics module time-to-launch reduced by 5 months

   

• Enterprise client NPS score increased by 18 points following the enhanced talent analytics release

   

• Data refresh latency reduced from weekly batch to real-time streaming for premium clients

   

Client Testimonial:
“Hir Infotech’s DaaS output is genuinely production-ready. Their team understood exactly what our product needed and built a delivery pipeline that plugs directly into our system. It saved us months of engineering work.”
— Chief Product Officer, HR Tech Company, Stockholm, Sweden

Client Background:
A multinational industrial manufacturing group with operations in Stuttgart, Germany and Lyon, France, sourcing components from 400+ global suppliers. Their procurement and supply chain teams needed a real-time supplier risk intelligence solution to mitigate disruptions.

Challenge:
Following multiple supply chain disruptions in 2023–2024, the company’s leadership mandated a proactive data-driven approach to supplier risk management. Their existing process — quarterly manual supplier reviews and reactive news monitoring — failed to catch early warning signals on supplier financial stress, geopolitical disruptions, and logistics bottlenecks.

Solution:
Hir Infotech built a DaaS feed delivering daily structured intelligence on 400+ named suppliers — monitoring financial distress signals (credit rating changes, late payments), logistics disruption data (port delays, shipping index feeds), news sentiment scoring, and regulatory compliance flags across 18 countries. Data was delivered to their SAP-integrated procurement dashboard via API.gleecus+1

Results:

• Identified 7 at-risk suppliers 45–90 days ahead of actual disruptions

   

• Procurement team avoided an estimated €2.3M in emergency sourcing costs in the first year

   

• Supplier review cycle time reduced from quarterly to continuous monitoring

   

• Compliance reporting time for EU supply chain due diligence regulations cut by 55%

   

Client Testimonial:
“Having Hir Infotech’s DaaS platform feeding real-time supplier intelligence into our procurement system has been a game-changer. We now act on risk signals early, not after a crisis hits.”
— Group CPO, Industrial Manufacturing, Stuttgart, Germany

Client Background:
A Sydney-based MedTech company developing AI-powered clinical decision support tools for Australian public and private hospitals. Their data science team required comprehensive, structured provider directory data and clinical practice information to build and validate their AI recommendation models.

Challenge:
Australia’s fragmented healthcare data landscape — spread across AHPRA, Medicare Benefits Schedule, state-level registries, and private hospital networks — made building a unified provider dataset extremely time-consuming. The company’s small data team lacked the capacity to source, aggregate, and maintain this infrastructure internally while also advancing their core product development.

Solution:
Hir Infotech delivered a structured, regularly refreshed DaaS feed covering 85,000+ registered Australian healthcare providers — including specialty classifications, practice locations, Medicare provider numbers, hospital affiliations, and clinical procedure volumes — normalized into a single schema and delivered monthly via secure SFTP with full audit logs for Australian Privacy Act compliance.

Results:

• Provider coverage expanded from 12,000 manually compiled records to 85,000+ within 60 days

   

• AI model accuracy for specialty routing improved by 34%

   

• Regulatory audit time for data provenance reduced by 70%

   

• Product team redirected 3 full-time data engineers to core ML development

   

Client Testimonial:
“Hir Infotech’s DaaS team delivered exactly what we needed — structured, reliable provider data that met our compliance requirements and integrated smoothly with our ML pipeline. Their turnaround time and support quality are outstanding.”
— Head of Data Science, MedTech Platform, Sydney, Australia

Client Background:
A mid-market consumer goods brand headquartered in Milan, Italy with retail distribution across Italy, Spain, and France. Their marketing and product teams needed structured consumer sentiment and review data to inform product development and regional campaign strategy.

Challenge:
Manually monitoring customer reviews across Google, Trustpilot, Amazon.it, Amazon.es, and regional retail platforms was inconsistent and slow — producing incomplete brand intelligence that lagged 2–3 weeks behind actual consumer conversations. The brand lacked a unified view of sentiment trends, product-level feedback, and competitor review benchmarking across Southern European markets.

Solution:
Hir Infotech’s DaaS team built a multilingual sentiment data pipeline ingesting 50,000+ reviews per month across 8 platforms in Italian, Spanish, and French — applying AI-driven sentiment classification, product attribute extraction, and competitor benchmarking. Weekly structured reports and a live dashboard delivered actionable insights into brand perception, product-level NPS drivers, and regional market differences.

Results:

• Brand review coverage increased from 3 platforms to 8 markets in 60 days

   

• Product team identified and resolved 3 major product defect patterns within weeks, reducing returns by 18%

   

• Marketing ROI improved by 27% following campaign messaging adjustments informed by sentiment data

   

• Time from insight to campaign adjustment reduced from 3 weeks to 5 days

   

Client Testimonial:
“Hir Infotech’s multilingual DaaS feed gave us a real understanding of how Southern European consumers feel about our products. The structured output made it incredibly easy for our team to act on the data.”
— Director of Consumer Insights, Consumer Goods Brand, Milan, Italy