01
Unclear GenAI use cases
Outcome: A prioritized roadmap tied to ROI — not a scattershot AI wish list.
How Spectrum helps
- Identify high-impact workflows and quick wins
- Define KPIs and success metrics upfront
- Align stakeholders on scope before build
Generative AI Development
Production-ready GenAI systems — built for your enterprise data, workflows, and compliance requirements. Not demos that never ship.
Partner the way that fits your program — a managed delivery team or a fixed-cost build.
- Managed team
Dedicated squad on your roadmap, tools, and cadence
- Fixed-cost delivery
Agreed scope, timeline, and price for the outcome
GenAI products and platforms, either engagement model.
Share your development need — we reply within one business day with scope, timing, and whether a managed team or fixed-cost delivery fits best.
Enterprise GenAI delivery partner
200+ Clients worldwide · 350+ Projects shipped
Problems we solve
The AI blockers holding teams back
Generative AI adoption stalls when use cases, integration, accuracy, or compliance are unclear. We help you move from pilots to production.
02
Hard to integrate with existing systems
Outcome: GenAI embedded in CRM, ERP, SaaS, and internal apps via API-first design.
How Spectrum helps
- API and middleware patterns that fit your architecture
- Compatibility with Salesforce, Dynamics, and custom stacks
- Scalable deployment across environments
03
Accuracy, hallucination & trust
Outcome: Reliable, explainable responses with validation and monitoring.
How Spectrum helps
- RAG pipelines over approved knowledge sources
- Output guardrails and evaluation harnesses
- Continuous tuning as content and policies change
04
Privacy, security & compliance
Outcome: Secure deployments aligned with your data residency and policy requirements.
How Spectrum helps
- Private cloud or VPC deployment options
- Role-based access and audit trails
- Security review integrated into delivery
What we do
Generative AI services we deliver
Copilots, agents, RAG, and custom apps — scoped for workflow impact, not novelty.
Inputs
Enterprise data
Policies & docs
User context
GenAI layer
Grounded & governed
Outputs
Grounded answers
Generated content
Workflow actions
Your data
RAG & fine-tune
Your stack
API-first fit
Guardrails
Human review
Production
Monitor & improve
Help teams work faster
AI copilot development
AskRetrieveActKnowledge and tasks in one place.
Multi-step execution
Agentic AI & automation
PlanExecuteReportLess manual orchestration.
Models that fit your domain
LLM engineering & tuning
AssessTuneEvaluateBetter relevance and control.
Answers from trusted sources
RAG knowledge assistants
IndexRetrieveCiteStaff and customers get facts.
Support at scale
Enterprise chatbots
IntentResolveEscalate24/7 coverage with handoff.
Purpose-built products
Custom GenAI applications
DesignBuildLaunchContent, docs, and decisions automated.
Not sure which to start with? We recommend one high-impact use case on the first call.
Share your requirementsHow we work
Our generative AI approach
A structured path from discovery and data readiness to production deployment and continuous improvement.
- 01
Discovery & use cases
Map goals, workflows, and constraints to define the right GenAI strategy and first release.
- 02
Data assessment & prep
Structure, clean, and govern enterprise data for accurate, context-aware model behavior.
- 03
Architecture & design
Design scalable solutions around security, integration, latency, and long-term maintainability.
- 04
Build & integrate
Develop models, RAG pipelines, copilots, and integrations inside your environment.
- 05
Test & deploy
Validate accuracy, performance, and workflow fit before production rollout.
- 06
Monitor & optimize
Track quality, cost, and drift — retrain and refine as your business evolves.
Our track record
AI excellence, backed by numbers
Measurable delivery for enterprises worldwide — skilled AI engineers, certified processes, and programs shipped at scale.
100+
Skilled AI engineers
200+
Clients worldwide
350+
AI & data programs
ISO 9001:2015
Quality certified
ISO 27001
Security certified
10+
Years in delivery
6
Global delivery hubs
Proof in production
Our success stories in Generative AI
Real programs — from conversational AI and voice assistants to enterprise copilots — shipped with measurable outcomes.
EnterpriseFeatured case study
AI-Powered Enterprise Automation
Deployed LLM agents and workflow orchestration across CRM, ERP, and documents — with guardrails, audit trails, and human review where decisions matter.
Result
40%+ Manual task reduction
PythonOpenAILangChainPostgreSQLREST APIsAzure
Read case study
Cloud ServicesAI Cloud Workload Assessment Product
Partners analyze customer workload cloud readiness and receive AI-driven migration step plans — assessment architecture built for scale.
Outcome
Weeks → Days per assessment
PythonOpenAIReactAWS+1
Read case study
FintechFintech Platform Modernization
We built a payment layer on top of existing infrastructure using a strangler-fig approach — SEPA instant processing, payment orchestration, and DORA compliance during a phased enterprise delivery.
Outcome
40% Faster time-to-market
JavaKubernetesKafkaPython+1
Read case study
Media & BroadcastVideo Analytics Platform
Platform for broadcasters and media companies to deliver monetized video — capturing, standardizing, synchronizing, and routing data to client endpoints at scale.
Outcome
Real-time Data routing
KubernetesKafkaReactNode.js+2
Read case study
Professional ServicesEnterprise GenAI Copilot Platform
Production RAG copilot over contracts, policies, and CRM notes — with citation-backed answers, role-based access, and usage governance for thousands of staff.
Outcome
10 wks Pilot to production
Azure OpenAILangChainPythonReact+2
Read case studyTechnical depth
Expertise our teams bring
LLM engineering, RAG, agents, and MLOps — delivered by architects who have shipped enterprise AI before.
- 01
LLM engineering & optimization
Model selection, fine-tuning, prompt systems, latency tuning, and cost control for production workloads.
- 02
Retrieval-augmented generation
Vector search, chunking strategies, and citation-ready answers from your knowledge bases.
- 03
Copilots & chatbots
Assistants for support, sales, HR, and operations — with escalation and human-in-the-loop paths.
- 04
Agentic & multi-agent systems
Agents that coordinate tools, APIs, and workflows with defined boundaries and approvals.
- 05
LLMOps & lifecycle management
Monitoring, evaluation, versioning, and governance across the full GenAI lifecycle.
- 06
Data engineering for GenAI
Pipelines, embeddings, and quality checks that keep AI inputs reliable and accessible.
Model landscape
Foundation models we work with
We are model-agnostic — choosing the right stack for accuracy, cost, privacy, and deployment constraints.
Technology
Stack for generative AI solutions
Orchestration, vector stores, cloud AI services, and MLOps tooling — selected for your environment.
LLM orchestration
- LangChain
- LlamaIndex
- LangGraph
- Semantic Kernel
RAG & vectors
- Pinecone
- Weaviate
- Chroma
- pgvector
- Elasticsearch
Cloud AI
- AWS Bedrock
- Azure AI
- Vertex AI
- SageMaker
MLOps & observability
- MLflow
- LangSmith
- PromptLayer
- Custom eval pipelines
Industries
Where GenAI creates measurable value
Tailored use cases for regulated and high-volume environments.
Banking & insurance
- Policy copilots
- Claims document processing
- Compliance Q&A
Healthcare & life sciences
- Clinical documentation assist
- Patient engagement bots
- Medical knowledge search
Retail & e-commerce
- Product content generation
- Shopping assistants
- Support automation
Manufacturing
- Workforce knowledge assistants
- Quality report summarization
- Maintenance guides
SaaS & technology
- In-product copilots
- Intelligent search
- Workflow automation
Logistics & supply chain
- Shipment inquiry bots
- Route planning assist
- Documentation automation
Why Spectrum
Why teams choose us for GenAI
Production delivery, enterprise integration, and governance — not slide-deck AI.
200+Happy Clients
End-to-end GenAI delivery
From discovery and architecture through deployment, integration, and post-launch optimization — one accountable partner.
Built for your enterprise stack
Every solution connects to CRM, ERP, knowledge bases, and workflows you already operate.
Security & compliance focus
Access controls, private deployment options, and audit-friendly practices from the first sprint.
Production-grade architecture
Monitoring, guardrails, evals, and a path to retraining so quality holds after go-live.
Managed team or fixed-cost
Scale with a dedicated squad or lock scope and price for a defined GenAI program.
Start smart
Pick your entry point
Most teams begin with a short working session, then move to a focused pilot or production rollout — managed team or fixed-cost, your choice at every step.
- Step 13–5 days· Kickoff window
Scope & align
We map one high-value use case, check data readiness, and agree on scope before any build spend.
Book a working sessionYou leave with
- Prioritized use cases
- Data readiness snapshot
- Timeline & cost range
- Step 22–3 weeks· Focused pilot
Prove it works
A working build on real sample data — enough to judge accuracy, UX, and business fit.
Plan a pilotYou leave with
- Live demo environment
- Eval results
- Production roadmap
- Step 34–6 weeks· From signed scope
Ship to production
Integrate with your CRM, ERP, or internal tools — with guardrails, monitoring, and handover.
Share your stackYou leave with
- Production deployment
- Monitoring & guardrails
- Runbook for your team
Same two models throughout: a managed delivery squad or a fixed-cost milestone plan.
Questions
Frequently asked questions
How do we know if generative AI is the right investment?
We start by mapping workflows where manual effort, slow decisions, or knowledge gaps create cost. If GenAI can measurably improve those areas, we define a pilot before larger spend.
What business problems can generative AI solve?
Common wins include support automation, internal knowledge access, document processing, content generation, reporting, and decision support — especially where speed and consistency matter.
Will GenAI work with our CRM, ERP, and internal systems?
Yes. We integrate via APIs and workflow tools so AI operates inside your current ecosystem rather than forcing a rip-and-replace.
How do you reduce hallucinations and inaccurate answers?
RAG over approved sources, validation rules, guardrails, evaluation sets, and human review for sensitive outputs — tuned to your domain over time.
How secure is generative AI for enterprise use?
We deploy with private environments, encryption, role-based access, and governance aligned to your security and compliance requirements.
Do we need a large internal AI team to manage this?
No. Most clients start with our team handling strategy, build, deployment, and optimization — then transfer knowledge to internal staff as you scale.
What's the difference between copilots, agents, and chatbots?
Copilots assist inside workflows. Agents execute multi-step tasks across systems. Chatbots focus on conversational support — we help you pick the right pattern per use case.
Can GenAI be customized for our workflows?
Yes. Systems are tailored to your data, policies, terminology, and approval paths so outputs are relevant and usable in production.
Build GenAI with Spectrum
Ready to ship generative AI to production?
Copilots, RAG assistants, and custom LLM apps — grounded in your data with guardrails and enterprise integration. Managed team or fixed-cost delivery.
100% confidential
We sign NDA
Same-day response
Prefer to validate first?
Explore an AI proof of concept