We connect n8n, CRM, Google Sheets, and Slack with AI integration services for business operations. You get agentic AI services for business operations that send a ranked daily action list plus handover notes.
We build one daily AI agent that checks your CRM, Google Sheets, and internal docs, ranks what needs attention, and sends a clear Slack action list.
Connects the agent to your CRM and Google Sheets so it can read the records needed each morning.
Your team now scans CRM records and Google Sheets by hand each morning to find items that need attention.
"Each morning, the agent pulls the latest CRM records and Google Sheets rows before the team starts its manual review."
Adds a short retrieval step so the agent checks internal documents before it writes its answer.
A daily list can miss company context when it relies only on CRM fields and spreadsheet rows.
"Before ranking a CRM item, Claude retrieves the relevant internal document passage and uses it to explain why it matters."
Turns the morning source data into a clear, ordered action list instead of another raw report.
The team must work out what needs attention after reading several sources, which delays the first useful decision.
"Claude reviews the morning CRM and Sheet data, then returns the highest-priority items with a reason for each."
Runs the daily agent in n8n and sends the finished action list to Slack each morning.
Even a useful action list adds work if someone must run the agent and move the result into Slack every day.
"n8n starts the agent each morning and posts the ranked action list into Slack for the team to review."
Documents the agent, prompts, connections, and routine changes your team may need to make.
The pilot will be hard to maintain if every prompt, source, or schedule change requires outside help.
"Your team can use the guide to update the priority prompt or change the Slack delivery point after handover."
Real engagements. Relevant to what you need.
AI Agent Development
Initial problem
Business teams spent 60% of decision-making time on low-complexity, rule-bound decisions — access approvals, payment releases, tier-1 escalations.
Our solution
AI agent development targeting decision automation: autonomous agents trained on historical decisions, business rules, and policy documents.
Result
83% of previously manual decisions now handled autonomously by AI agents; senior team decision load reduced by 60%.
"The business outcome is that our team now touches only decisions that genuinely require human insight. That ratio shift is transformative."
AI Agent Development
Initial problem
Invoice approval across 6 systems — ERP, Slack, legal, and payment — took 3–5 business days with constant manual coordination.
Our solution
Built a custom AI agent development solution using LangChain and CrewAI: autonomous agents that extract invoice data, match against POs.
Result
Standard invoice processing time reduced from 3-5 days to under 4 hours; autonomous ai agents handle 84% of invoices without human intervention.
"The AI agents handle extraction, matching, routing, and ERP sync without human input on standard cases. Estimated 1,200 hours per quarter saved."
AI Agent Development
Initial problem
Sales operations team spent 50% of their time on manual lead scoring, CRM field updates, and follow-up task creation — non-value-adding work.
Our solution
Built AI agent development for revenue operations: autonomous AI agents that enrich lead data, apply a proprietary scoring model, update.
Result
Lead score latency reduced from 48 hours to under 30 minutes; sales ops team fully exited from manual crm maintenance.
"Leads are scored, updated, and queued automatically. Our sales team now acts on intelligence rather than creating it."
Business ops leads get a reviewed morning Slack action list grounded in CRM, Google Sheets, and internal documents.
Companies we've worked with
Oxagile
AI Agent Development
US
A3Logics
AI Agent Development
US
Markovate
AI Agent Development
US
ScaleTech Solutions
AI Agent Development
US
Altoros
AI Agent Development
US
Netguru
AI Agent Development
PL
"The business outcome is that our team now touches only decisions that genuinely require human insight. That ratio shift is transformative."
S. Marchuk
Founder & CTO · Oxagile
"The AI agents handle extraction, matching, routing, and ERP sync without human input on standard cases. Estimated 1,200 hours per quarter saved."
A. Sharma
CEO & President · A3Logics
"Leads are scored, updated, and queued automatically. Our sales team now acts on intelligence rather than creating it."
R. Sharma
Co-Founder & CEO · Markovate
"CogWorkLabs built AI agent development where autonomous agents watch our data pipelines, trigger remediation on failures, and generate client-facing reports automatically. Data analysts now do data analysis — not operations."
R. Flickinger
Managing Partner · ScaleTech Solutions
These use cases cover morning triage, grounded priorities, and reviewed Slack handoffs — the daily work this agent takes on.
Current problem
Every morning, your team opens the CRM and scans records by hand before it can decide what deserves attention.
Automated workflow
The agent reads current CRM records through the configured API or MCP connection, then adds the relevant items to the daily review list.
Human involvement
Your team reviews the ranked CRM items in Slack and decides what action to take.
Systems
Possible outcome
The team starts with a focused CRM review instead of a full scan.
Our AI development services for business operations move this CRM, Sheets, RAG, and Slack pilot through six clear phases.
We map the morning CRM and Google Sheets scan, the internal docs used, and how the team decides what needs attention.
Join a 60-minute workflow call, share sample CRM records, Sheet rows, and the internal docs used in review.
We check whether CRM, Google Sheets, Claude, and MCP access can support the daily read and short internal-doc RAG step.
Provide test access details and confirm which CRM records, Sheet rows, and internal docs the pilot may read.
We document source pulls, the RAG step, priority rules, the review gate, and the n8n-to-Slack delivery path.
Approve the priority rules, document sources, Slack destination, and what the agent must never act on.
We run a working slice on real CRM records, Sheet rows, and internal docs, then post a test action list to Slack.
Review the test Slack brief, mark weak rankings, and confirm whether the cited internal context is useful.
We build the Claude agent, RAG flow, API or MCP connections, n8n schedule, Slack post, and review checks.
Run user acceptance testing with the ops team and approve production credentials and final prompt changes.
We launch the morning run, watch for CRM, Sheets, Claude, n8n, and Slack failures, and hand over the adjustment guide.
Attend go-live review, name an alert owner, and confirm the post-launch support window.
A 30-minute discovery call is enough to map your workflow and tell you whether automation makes sense.
We protect the morning CRM-to-Slack brief from bad rankings, silent data gaps, and changes made without review.
We review every suggested CRM or Google Sheets action with you before it moves beyond the Slack brief, so the pilot never acts alone.
How we prove it
Slack approval step documented before the pilot goes live.
We take no referral fees from AI or automation vendors. We map Claude, n8n, your CRM, and Sheets first, then recommend what fits.
How we prove it
Design doc lists tool options with tradeoffs before build.
We watch the daily CRM, Google Sheets, and Slack path, so a missed run or dropped connection is caught before your team loses the morning brief.
How we prove it
Monitoring dashboard included; 30-day post-launch support.
We scope this first pilot and any later modules separately before code starts, so each week's work and scope stay visible.
How we prove it
Signed pilot scope and weekly build updates.
A few words from the teams we've partnered with, sharing what it's been like to work with us and the impact automation has had on their day-to-day.
"The business outcome is that our team now touches only decisions that genuinely require human insight. That ratio shift is transformative."
83% of previously manual decisions now handled autonomously by AI agents; senior team decision load reduced by 60%.
S. Marchuk
Founder & CTO · Oxagile
"The AI agents handle extraction, matching, routing, and ERP sync without human input on standard cases. Estimated 1,200 hours per quarter saved."
Standard invoice processing time reduced from 3-5 days to under 4 hours; autonomous ai agents handle 84% of invoices without human intervention.
A. Sharma
CEO & President · A3Logics
"Leads are scored, updated, and queued automatically. Our sales team now acts on intelligence rather than creating it."
Lead score latency reduced from 48 hours to under 30 minutes; sales ops team fully exited from manual crm maintenance.
R. Sharma
Co-Founder & CEO · Markovate
Our AI development services for business operations fit teams that check CRM records, Google Sheets, and internal docs each morning.
Ops teams compare CRM activity, account notes, and planning sheets each morning; the agent ranks follow-ups and posts one reviewed action list to Slack.
A SaaS ops lead gets ranked renewals, stalled deals, and overdue follow-ups in Slack each morning.
Recruiters track candidate and client follow-ups across CRM records, Sheets, and process notes; the agent ranks the next calls and review items.
A staffing team gets a Slack list of stalled candidates, client replies, and records needing review.
Sales and ops teams check account records, order sheets, and internal procedures for exceptions; the agent highlights urgent follow-ups without changing source data.
A distributor sees delayed orders, account issues, and owner follow-ups ranked in Slack.
Property teams review tenant records, issue sheets, and operating guides each morning; the agent ranks open cases and sends the action list to Slack.
A property manager gets ranked maintenance cases, lease follow-ups, and records needing review.
These FAQs explain how our AI development services for business operations pilot is scoped, built, reviewed, and handed over.
You'll work with named engineers and a dedicated delivery manager — not an anonymous team bench.
Awais Shahid
Automation Consultant & Solutions Advisor
Awais runs discovery, maps your process, and turns it into a scoped, build-ready plan for custom scripting and automation — staying your one named point of contact through sign-off.
Experience
Zegham Ali
AI Agent & LLM Engineer
Zegham designs the AI agents themselves — scoped permissions, bounded memory, evals, and monitoring — so an agent stays observable and safe in production, not just impressive in a demo.
Experience
Zeeshan Ahmad
Founder & Principal Automation Architect
Zeeshan owns the architecture behind every build — choosing the stack, designing the integrations, and deciding where reliability layers like failure handling and human review gates need to sit before a system goes live.
Experience
Book a 30-minute discovery call. We'll map your current workflow and tell you exactly what we'd automate — and whether it's worth building.
