Claude
by AnthropicDocument and email intake (RFQs, purchase orders, invoices) parsed into strict schemas with citations, and a read-only “talk to your data” assistant.
Data, automation and integrations
Data, analytics and automation
Turn scattered data and repetitive work into dashboards, pipelines and reviewed automations.
What we deliver
We connect your data sources into reliable pipelines and dashboards, and automate repetitive work such as document intake, email triage, reconciliation and reporting, with AI where it helps and human review where it matters.
No public case study yet · see how an engagement runsData you can trust
Pipelines from your apps, spreadsheets and databases into a warehouse such as BigQuery or Postgres, modelled into clear metrics, with dashboards your team actually opens.
Plain-language analytics: a “talk to your data” assistant on a read-only connection, so managers can ask questions without writing SQL.
Automation with review
Document and email workflows (RFQs, purchase orders, invoices, KYC packs) parsed into structured data, checked against your rules and written to your CRM, ERP or accounting system after approval, including TallyPrime through its HTTP/XML interface.
Every automation has an owner, an audit trail and an off switch.
Where we are
This practice is newer than our web and commerce work, and we don't yet have a public data-platform case study, so this page shows how an engagement typically runs instead. In a first call we'll show you the approach, reference architectures and the people involved.
Typical deliverables
- Data audit and metric definitions
- Pipelines into BigQuery, Postgres or Snowflake
- Dashboards in Looker Studio, Metabase or custom
- Document and email automation with approval steps
- “Talk to your data” assistant on read-only access
- Monitoring, alerts and documentation
Tools we typically use
- BigQuery
- Postgres and Supabase
- Snowflake
- dbt
- Looker Studio
- Metabase
- Claude and Gemini for extraction and classification
- n8n or custom workers
- TallyPrime, Zoho and HubSpot APIs
If your team already runs a different stack, we work within it. These are defaults, not requirements.
Claude and Gemini
Where Claude and Gemini fit
We build on both model families and choose per task, on evaluation results, cost and latency, inside the cloud you already use.
Gemini
by GoogleReading scans, photos and video at volume, and Gemini options that sit natively alongside BigQuery.
Together. Whichever model reads the document, a person approves before anything is written to a system of record.
Phases and team
How an engagement typically runs
3–12 weeks, delivered by a small senior pod, with progress you can see as it is built. Pip tailors the working model to your team.
Audit
Map your data sources, the questions your team needs answered and the repetitive work worth automating.
First pipeline and dashboard
One reliable pipeline and one dashboard your team actually opens, before anything else is built.
Automation with review
Document and email workflows with an approval step before anything reaches a system of record.
Run and improve
Monitoring, alerts and documentation, with new sources and automations added as they prove their value.
Typical team
Data architect, data engineer, analytics engineer and a QA engineer
Pricing
Priced to your scope and market.
Every project is priced to its scope and market. Pip gives you a tailored range in minutes, and the final number comes in a written proposal.
Hosting, subscriptions, licences and AI usage are billed to your own accounts at cost, estimated up front.
Related work
Case studies
We don't have a public case study for this service yet. Rather than invent one, we've set out above how an engagement typically runs. On a call we'll walk you through the approach and introduce the people who would do the work.
FAQ
Data and automation: common questions
Ask Pip if yours isn't here.
Not always. If your questions span several systems or need history, yes. If one database already holds what you need, we build on it directly.
We design automations to remove repetitive steps and leave decisions with people. Most of the workflows we design include an approval step before anything is written to a system of record.
Yes. TallyPrime supports integration over HTTP with XML or JSON, so we can build connectors for invoice, ledger and reconciliation workflows.
Further reading
Solution playbooks that use this service
Playbooks are reference architectures we propose for an industry, not past client results.
- Playbook · Real estateLease and property document abstractionExtract parties, rent schedules, escalations, lock-ins and renewal dates from leases and property documents with Claude, every field linked to the page it came from.
- Playbook · Manufacturing and B2BRFQ-to-quote and PO intake automationRead RFQs and purchase orders from email, PDFs and spreadsheets, map line items to your item master, draft quotes for approval and write orders to SAP, Tally or Zoho.
- Playbook · Finance and accountingInvoice-to-Tally and GST reconciliation assistantExtract purchase-invoice data from PDFs and photos, post approved vouchers to TallyPrime, chase vendors on WhatsApp and clear GST mismatches before filing.
- Playbook · Any industry“Talk to your data” analystLet business users question Postgres, BigQuery or Snowflake in plain language, with read-only access, a semantic layer, charts and an evaluation set before rollout.
- Playbook · Healthcare and life sciencesClinical and regulatory document draftingDraft protocols, SOPs, discharge summaries and submission sections from approved sources with Claude, with citations, template checks and expert sign-off.
- Playbook · Retail and e-commerceCatalogue and content factoryBatch-generate product descriptions, attributes, alt text, translations and on-brand imagery for thousands of SKUs with Claude and Gemini, with a human review queue.
Related services
All services
Integrations and APIs
Connect your CRM, ERP, commerce, payments and messaging so data moves once, correctly.
Case studies: THE SUNYA
- Typical timeline
- 3–12 weeks
AI agents and automation
Agents that answer, act and hand off, on Claude and Gemini, inside the tools you already run.
Case studies: LuxeLens AI Studio
- Typical timeline
- 4–10 weeks
Cloud and DevOps on Google Cloud
Secure, observable infrastructure on Google Cloud and Vercel, with deployments that are boring in the best way.
Case studies: LuxeLens AI Studio
- Typical timeline
- 3–12 weeks
Pip · Softpiper's AI
Ask Pip
Get a tailored range in a couple of minutes
Pip is Softpiper's AI. Describe the project and it will ask a few questions, give you a tailored price range for your scope and market, and book a call with the team.