"Agile Infoways team delivered exceptional iOS and Android apps with responsive support and outstanding problem-solving expertise."
- Rob Machado
AI EngineeringAI Integration & Copilots
Embed AI Copilots into Every Workflow Your Team Uses
Integrate AI assistants directly into Microsoft 365, Salesforce, Slack, and your custom apps — so your teams get AI-powered help exactly where they work, without switching context.
Copilot Capabilities
AI Integration & Copilot Development
From API wrappers to deeply embedded AI copilots, we build assistants that augment your team's capabilities where they work.
Custom AI Copilots
Purpose-built copilots trained on your domain knowledge — a legal copilot for contracts, a finance copilot for analysis, a code copilot for your stack.
Enterprise Platform Integration
Embed AI into Microsoft 365 Copilot, Salesforce Einstein, ServiceNow, Slack, Teams, and any custom SaaS platform via native APIs.
LLM API Integration
Production-grade integrations with OpenAI, Anthropic, Google Gemini, and Azure OpenAI — with fallback routing, rate limiting, and cost controls.
Multi-Persona Assistants
Single assistant platform with persona switching — the same backend powering different copilot experiences for sales, support, and engineering teams.
Usage Analytics & Governance
Track copilot adoption, measure productivity gains, monitor prompt quality, and enforce enterprise usage policies from a central dashboard.
Enterprise Security & SSO
SAML/OAuth SSO, role-based access, data residency controls, and end-to-end encryption to meet enterprise security requirements.
Why Choose Us
Why Agile Infoways for AI Copilots
We've deployed copilots used by 50,000+ enterprise users with 90%+ daily active usage rates.
Adoption-Focused Design
Copilots succeed only if teams use them. We design for workflow fit, not just technical capability — optimizing for daily active usage.
Platform Partnership
Microsoft, Salesforce, and ServiceNow certified integration specialists who know the APIs, limits, and best practices deeply.
Measurable Productivity Gains
We instrument every copilot to measure time saved, quality improvement, and task completion rates — proving ROI to stakeholders.
Iterative Rollout Strategy
Start with one team or use case, measure impact, then scale. No big-bang deployments — just validated, expanding value.
Our Capability
Integration Stack
Proven connectors and frameworks for embedding AI into every enterprise platform.
Microsoft Graph API
Deep M365 integration: emails, calendars, SharePoint, Teams, and OneDrive access for copilots.
Slack / Teams Bots
Native bot frameworks with rich message formatting, interactive components, and file handling.
OpenAI / Anthropic APIs
Production API integrations with caching, fallback chains, and token cost optimization.
Salesforce Einstein
Einstein Platform integration for CRM-aware copilots with Apex and Flow triggers.
LangChain / LlamaIndex
Flexible frameworks for building context-aware copilots with tool use and memory.
Streaming Response APIs
Server-sent events and WebSocket streaming for real-time, low-latency copilot UX.
Our ApproachHow We Build
How We Build
AI Copilots
From use-case definition through enterprise rollout with adoption measurement at every stage.
01
Use-Case & Platform Workshop
02
Prototype & User Testing
03
Production Build & Integration
04
Rollout & Adoption Program
Step 01
Use-Case & Platform Workshop
Identify the highest-value copilot use cases, map to the platforms your teams already use, and define success metrics and governance requirements.
Use-case prioritizationPlatform selectionSuccess metricsGovernance policy
Step 02
Prototype & User Testing
Build a working copilot prototype with real users in 2–3 weeks. Collect feedback on UX, response quality, and workflow fit before full development.
2-week prototypeUser feedback sessionsPrompt optimizationUX refinement
Step 03
Production Build & Integration
Full-scale development with enterprise SSO, data access controls, audit logging, and native integration into target platforms.
Enterprise SSOAudit loggingPlatform integrationPerformance testing
Step 04
Rollout & Adoption Program
Staged rollout starting with pilot team, training sessions, internal champions program, and monthly adoption reporting to stakeholders.
Pilot team rolloutTraining materialsChampions programAdoption dashboards
Our ApproachHow We Build
How We Build
AI Copilots
From use-case definition through enterprise rollout with adoption measurement at every stage.
Step 01
Use-Case & Platform Workshop
Identify the highest-value copilot use cases, map to the platforms your teams already use, and define success metrics and governance requirements.
Use-case prioritizationPlatform selectionSuccess metricsGovernance policy
Step 02
Prototype & User Testing
Build a working copilot prototype with real users in 2–3 weeks. Collect feedback on UX, response quality, and workflow fit before full development.
2-week prototypeUser feedback sessionsPrompt optimizationUX refinement
Step 03
Production Build & Integration
Full-scale development with enterprise SSO, data access controls, audit logging, and native integration into target platforms.
Enterprise SSOAudit loggingPlatform integrationPerformance testing
Step 04
Rollout & Adoption Program
Staged rollout starting with pilot team, training sessions, internal champions program, and monthly adoption reporting to stakeholders.
Pilot team rolloutTraining materialsChampions programAdoption dashboards
Use Cases
Copilot Deployments
Real AI copilot implementations driving measurable productivity gains.
SA
SalesSales Intelligence Copilot
The Challenge
Sales reps spending 30% of time on CRM data entry and call prep instead of selling.
The Outcome
Salesforce-integrated copilot auto-logs calls, suggests next actions, and drafts follow-up emails — saving 90 minutes per rep per day.
Salesforce EinsteinGong integrationGPT-4oEmail drafting
LE
LegalContract Review Copilot
The Challenge
Legal team taking 5 days to review standard NDAs, slowing deal velocity across the business.
The Outcome
Word-embedded copilot reviews NDAs in minutes, flags risky clauses, and suggests standard redlines — reducing review time by 80%.
Word add-inRAGClause detectionRisk scoring
IT
IT SupportIT Helpdesk Copilot
The Challenge
IT support team resolving 300 tickets daily with average resolution time of 4 hours.
The Outcome
Teams-integrated copilot resolves 65% of tickets autonomously, cutting average resolution time to 45 minutes.
Microsoft TeamsServiceNowTicket classificationSelf-service
FI
FinanceFP&A Analysis Copilot
The Challenge
Finance analysts taking 2 days to produce variance analysis reports from raw ERP data.
The Outcome
Excel copilot pulls ERP data, runs variance analysis, and generates narrative commentary — compressing 2 days to 2 hours.
Excel add-inSAP connectorChart generationNarrative AI
Industries
AI Solutions Across Key Verticals
Deep domain expertise meets cutting-edge AI — delivering results where they matter most.
Before You Build
Evaluating AI Copilots
What teams ask before embedding AI into their tools — what it is, build vs buy, platforms, security, adoption, and cost.
6 questions answered
01
What is AI integration, and what does an enterprise copilot actually do?
AI integration embeds AI directly into the tools your team already uses — Microsoft 365, Salesforce, Slack, or custom apps — instead of bolting on a separate chatbot. An enterprise copilot then drafts, summarizes, answers, and takes actions in context, grounded in your data. It's the difference between a generic assistant and AI copilots that know your business.
02
Should we build a custom copilot or use an off-the-shelf one like Microsoft 365 Copilot?
Off-the-shelf copilots like Microsoft 365 Copilot are great for general productivity, but they don't know your proprietary data, workflows, or rules. A custom copilot is the right call when you need answers grounded in your own systems, domain logic, or tighter access control. Most enterprises run both — generic for broad tasks, custom built on RAG for what matters.
03
Which platforms and tools can you embed AI into?
We embed AI into Microsoft 365, Salesforce, Slack, Microsoft Teams, ServiceNow, and your custom web and mobile apps — through native APIs, plugins, and SSO. The copilot lives inside the interface your team already uses, so there's no new tool to learn. CRM and ERP copilots tie into ERP and CRM systems for deeper workflow automation.
04
Is our data safe when we connect an LLM, and where does it go?
Yes — enterprise AI integration keeps your data controlled. We can route requests to private or self-hosted models so content never trains a public model, enforce your existing permissions and SSO, and redact sensitive fields before they reach the LLM. Every interaction is logged for audit. This security and governance is built on our AI infrastructure.
05
How do you make sure employees actually use the copilot?
Adoption comes from embedding the copilot where work already happens and designing it around real user tasks, not a generic chat box. We prototype with actual users, focus on a few high-value use cases first, and refine from usage analytics. Pairing it with familiar conversational AI patterns keeps the learning curve near zero and drives daily use.
06
How much does a custom copilot cost, and how long until it’s live?
A first production copilot is typically live in 6–8 weeks, then expanded use case by use case. Cost depends on the platforms to integrate, data sources to connect, and the depth of actions the copilot performs — scoped per rollout, not per seat. Many teams accelerate delivery with dedicated AI/ML engineers embedded in their team.
Client Stories
Built With Trust. Proven in Production.
Hear directly from the leaders who partnered with us to ship AI-powered products, modernize platforms, and move faster than they thought possible.
"Great company with great management quality developers were really dedicated to get the job done in a timely cost-effective manner."
- Alexandar Salahsour
"They consistently delivers reliable, high-quality development solutions with exceptional communication, value, and trusted partnership."
- Joe Pellegrino, Jordan Pellegrino
Proven in production80%faster contract & document review
A legal team replaced a 5-day NDA review cycle with a Word-embedded copilot that flags risky clauses and suggests redlines in minutes — no change to how they work.
Get In Touch
Let's Build Something Remarkable Together
Book a call or drop us a message. Our team will respond within 24 hours.
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