AI Development
NLP / Text Analytics Development
We build NLP and text analytics features that turn messy text into structured signals—classification, extraction, summarisation, and search—integrated into your product with measurable quality.
Overview
What this service is
This service designs a text analytics workflow: input sources, taxonomy, model approach (LLM or classic), and an implementation that handles real-world text variability.
We implement pipelines for batch or real-time processing, integrate outputs into your systems, and build evaluation so quality is visible and improvable.
You get a maintainable setup with monitoring and guidance on improving prompts/models and expanding coverage over time.
Benefits
What you get
Automate manual triage work
Classify and route tickets, requests, or messages without human bottlenecks.
Extract structured fields reliably
Turn free-text into JSON fields your systems can use for workflows and reporting.
Better search and discovery
Improve search relevance and content grouping with embeddings and text signals.
Quality you can measure
Evaluation harness so improvements are tracked instead of subjective.
Flexible model strategy
Choose LLM or lighter models based on cost, latency, and accuracy needs.
Production-ready integration
Pipelines and APIs designed to run reliably in real workloads.
Features
What we deliver
Taxonomy + labeling strategy
Define categories, entities, and fields—and plan data labeling or prompt strategy.
Classification and routing
Models or prompt workflows for classifying text into meaningful operational categories.
Entity and field extraction
Extract structured fields with validation and confidence handling for production use.
Summarisation and insights
Generate concise summaries, key points, and action items aligned to your team’s needs.
Embedding-based search (optional)
Semantic search and clustering for better discovery and grouping of unstructured content.
Evaluation + monitoring
Quality tracking, drift checks, and monitoring hooks so the system improves over time.
Process
How we work
Discovery
We review sample text, define outcomes, and choose an approach based on constraints and accuracy needs.
Design
We define taxonomy, extraction fields, and evaluation approach before building pipelines.
Build
We implement classification/extraction pipelines and integrate outputs into your systems.
Evaluation
We test against representative cases, measure quality, and iterate until results are stable.
Launch + Handoff
We ship monitoring and documentation so the system can improve and expand over time.
Tech Stack
Technologies we use
Core
Tools
Services
Use Cases
Who this is for
Support ticket classification
Auto-label and route tickets to the right queue with summaries for faster response.
CRM enrichment from emails
Extract contacts, intents, and key details from inbound communication into structured CRM fields.
Compliance text processing
Flag policy violations and extract evidence from documents and conversations.
Document summarisation workflows
Summarise contracts, proposals, and reports into structured brief outputs.
Semantic search for knowledge bases
Improve discovery of relevant docs and topics with embedding-based search patterns.
FAQ
Frequently asked questions
It depends on accuracy, latency, and cost constraints. We often start with LLM-based extraction and evaluate whether lighter models can meet requirements at scale.
Yes. We can scope privacy constraints and implement access control and data handling rules aligned to your requirements.
Yes. We build an evaluation harness so quality is measurable and improvements are tracked.
Yes. We can support real-time APIs or batch pipelines depending on volume and latency needs.
Yes. We integrate results into CRMs, ticketing, dashboards, or data stores using APIs and webhooks.
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Regional
Delivery considerations for your region
Compliance & Data (US)
For US teams, we build with auditability in mind: clear access boundaries, least-privilege roles, and reviewable operational controls.
We can align delivery with SOC 2 / ISO-friendly practices (without claiming certification): evidence-ready logs, secure-by-default config, and clear ownership.
- SOC 2 / ISO-friendly implementation patterns (no certification claims)
- Least-privilege access and permission boundaries
- Security review checklists for auth, payments, and data flows
- PII-safe logging + incident response playbooks (on request)
- Retention and deletion flows where required
- NDA + vendor onboarding docs on request
Timezone & Collaboration (Americas)
We support teams across the Americas with meeting windows that work for EST/CST/MST/PST.
We keep delivery predictable with weekly milestones, concise async updates, and written decisions to reduce calendar load.
- Americas overlap with EST/PST-friendly windows
- Async-first updates with written decisions
- Weekly milestone demos + change control
- Fast turnaround on blockers and clarifications
- Clear owner per workstream and escalation path
Engagement & Procurement (US)
US-friendly engagement structure: clear SOWs, milestone billing, and invoice cadence that fits typical procurement workflows.
If you need vendor onboarding artefacts, we can provide security posture summaries and delivery process documentation.
- USD invoicing and milestone-based payment schedules
- SOW + scope lock options for fixed-scope work
- Time-and-materials for evolving requirements
- Procurement-ready documentation on request
- Optional paid discovery to de-risk delivery
Security & Quality (US)
We ship with a security-first checklist and performance budgets—so releases stay stable under real traffic.
Expect clean PRs, reviewable changes, and production-ready testing from day one.
- Threat-aware checks for auth, roles, and sensitive data flows
- CI-friendly testing: unit + integration + critical path smoke tests
- Performance budgets (Core Web Vitals-minded) and bundle checks
- Structured logging + error tracking hooks (Sentry-ready)
- Rollback-safe releases and clear release notes
Need insights from text at scale?
Share sample data and outcomes you want (labels, fields, summaries). We’ll propose an NLP approach and delivery plan.
Evaluation + integration guidance included.